diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs000.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs000.html index 39a7c6c43..b1cd969e8 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs000.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs000.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • @@ -285,7 +285,7 @@ MathJax.Hub.Config({
    [2] Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University

    -

    Nov 10, 2019

    +

    Nov 11, 2019


    diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs001.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs001.html index 020ba0890..c64a99e8a 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs001.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs001.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({

  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs002.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs002.html index f39b144d4..0ff176617 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs002.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs002.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs003.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs003.html index 615f518a3..711d3db2c 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs003.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs003.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs004.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs004.html index d10bc9026..51de6dd3a 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs004.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs004.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs005.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs005.html index 6110977b0..d9017f99d 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs005.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs005.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs006.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs006.html index 08579e547..54ecd74cb 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs006.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs006.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs007.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs007.html index 973d9cfd9..6008fa889 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs007.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs007.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs008.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs008.html index 3f4594277..b98b9369d 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs008.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs008.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs009.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs009.html index 2704094d8..382b83c55 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs009.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs009.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs010.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs010.html index 88f46e5ae..bbff5560a 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs010.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs010.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs011.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs011.html index c70fa55d6..bb9e2857c 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs011.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs011.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs012.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs012.html index 21388431c..4d264f91c 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs012.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs012.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs013.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs013.html index af177e3f3..a33ead00d 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs013.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs013.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs014.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs014.html index 3559b2d81..50a90ff1b 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs014.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs014.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs015.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs015.html index 85fa0c3e7..7aad9b445 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs015.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs015.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs016.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs016.html index 4bb186d4f..6b522116e 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs016.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs016.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs017.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs017.html index bd7b75001..ce6404038 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs017.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs017.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs018.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs018.html index 5c166ac71..e52a30779 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs018.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs018.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs019.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs019.html index a96f1adc7..7e8d938c9 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs019.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs019.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs020.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs020.html index 0e40e84e6..76fd563dc 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs020.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs020.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs021.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs021.html index f41b68e3f..645a3f990 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs021.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs021.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs022.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs022.html index 0ef377ff9..bf5f2f8c3 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs022.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs022.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs023.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs023.html index 9c22332ff..d11ef26e5 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs023.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs023.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs024.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs024.html index 66e3f6c03..6e205d2a7 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs024.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs024.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs025.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs025.html index 7d8cd178a..c425838c8 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs025.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs025.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs026.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs026.html index 33eb58512..6f0a90299 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs026.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs026.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs027.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs027.html index 24477fabf..f490442a4 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs027.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs027.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs028.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs028.html index db67c522c..38d4171c1 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs028.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs028.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs029.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs029.html index 8b4f0cb2d..e92deff5f 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs029.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs029.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs030.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs030.html index 7cdf1a908..ed9f87b49 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs030.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs030.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs031.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs031.html index 743fe7e25..f5e04b9ef 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs031.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs031.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs032.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs032.html index 42a5b09a5..0aef23b71 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs032.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs032.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs033.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs033.html index 38eb671aa..4bd6b7b6c 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs033.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs033.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs034.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs034.html index 223ffdebf..e3645d6c5 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs034.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs034.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs035.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs035.html index 0faebab83..23d3432a4 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs035.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs035.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs036.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs036.html index c63bad3ce..051eea3d5 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs036.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs036.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs037.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs037.html index dadb9d6b0..8013401f5 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs037.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs037.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs038.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs038.html index 2fbf3909c..5a69776bd 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs038.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs038.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs039.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs039.html index 43b55b06b..8829cc78c 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs039.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs039.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs040.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs040.html index 4cb7a033c..125faf41b 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs040.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs040.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs041.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs041.html index 403714f96..13eb76736 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs041.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs041.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs042.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs042.html index 134430144..6253f401d 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs042.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs042.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs043.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs043.html index 52938a941..2e5aec99c 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs043.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs043.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs044.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs044.html index 0a0c842a0..66cd83100 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs044.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs044.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs045.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs045.html index cf134e215..260c9ddd7 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs045.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs045.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs046.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs046.html index ac4baa3f5..47ca444c3 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs046.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs046.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs047.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs047.html index c0336091e..48d23ca4a 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs047.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs047.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • @@ -278,7 +278,7 @@ The way we proceed is as follows (here we specialize to the squared-error cost f
    1. minimize \( \sum_{i=0}^{n-1}(y_i-f_{m-1}(x_i)-\beta b(x;\gamma))^2 \) wrt \( \gamma \) and \( \beta \)
    2. -
    3. This gives the optimial values \( \beta_m \) and \( \gamma_m \)
    4. +
    5. This gives the optimal values \( \beta_m \) and \( \gamma_m \)
    6. Determine then the new values \( f_m(x)=f_{m-1}(x) +\beta_m b(x;\gamma_m) \)
    diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs048.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs048.html index 2f0910c8f..ada510754 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs048.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs048.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • @@ -266,7 +266,7 @@ MathJax.Hub.Config({ -

    Squared Error Exampe and Iterative Fitting

    +

    Squared-Error Example and Iterative Fitting

    To better understand what happens, let us develop the steps for the iterative fitting using the above squared error function. @@ -275,7 +275,7 @@ To better understand what happens, let us develop the steps for the iterative fi For simplicity we assume also that our functions \( b(x;\gamma)=1+\gamma x \).

    -This means that for every iteration, we need to optmize +This means that for every iteration, we need to optimize $$ (\beta_m,\gamma_m) \mathrm{argmin}_{\beta,\lambda}\hspace{0.1cm} \sum_{i=0}^{n-1}(y_i-f_{m-1}(x_i)-\beta b(x;\gamma))^2=\sum_{i=0}^{n-1}(y_i-f_{m-1}(x_i)-\beta(1+\gamma x_i))^2. @@ -293,7 +293,7 @@ $$ \frac{\partial {\cal C}}{\partial \gamma} =-2\sum_{i}\beta x_i(y_i-\beta(1+\gamma x_i))=0. $$ -We can then rewrite these equations as (defining \( w_i=1+\gamma x_i) \) +We can then rewrite these equations as (defining \( \boldsymbol{w}=\boldsymbol{e}+\gamma x_i) \) with \( \boldsymbol{e} \) being the unit vector) $$ \gamma \boldsymbol{w}^T(\boldsymbol{y}-\beta\gamma \boldsymbol{w})=0, $$ @@ -304,7 +304,7 @@ $$ $$

    -which leads \( \gamma =(\boldsymbol{x}^T\boldsymbol{y}-\beta\boldsymbol{x}^T\em{e})/(\beta\boldsymbol{x}^T\boldsymbol{x}) \). Inserting +which leads to \( \gamma =(\boldsymbol{x}^T\boldsymbol{y}-\beta\boldsymbol{x}^T\boldsymbol{e})/(\beta\boldsymbol{x}^T\boldsymbol{x}) \). Inserting for \( \beta \) gives us an equation for \( \gamma \).

    diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs049.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs049.html index 3c9f43bb2..d067271a0 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs049.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs049.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({

  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • @@ -266,7 +266,7 @@ MathJax.Hub.Config({ -

    Iterative Fitting, Classification, AdaBoost

    +

    Iterative Fitting, Classification and AdaBoost

    Let us consider a binary classification problem with two outcomes \( y_i \in \{-1,1\} \) and \( i=0,1,2,\dots,n-1 \) as our set of diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs050.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs050.html index c1ce98823..210eb2e34 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs050.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs050.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({

  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs051.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs051.html index 368345bff..c2411b8f1 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs051.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs051.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs052.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs052.html index 2e71bf81d..b7c7ee3c9 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs052.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs052.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs053.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs053.html index bd612b14e..4d9388966 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs053.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs053.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs054.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs054.html index 45e976c1e..22955d15d 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs054.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs054.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs055.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs055.html index 835ee26e1..b59026eb8 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs055.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs055.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • @@ -269,7 +269,7 @@ MathJax.Hub.Config({

    Gradient boosting: Basics

    -Gradient boosting is again a similar technique to Adapative boosting, +Gradient boosting is again a similar technique to Adaptive boosting, it combines so-called weak classifiers or regressors into a strong method via a series of iterations. diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs056.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs056.html index 14623a2c8..4a6f767cb 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs056.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs056.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({

  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs057.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs057.html index e35744ad7..f4d69394d 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs057.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs057.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs058.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs058.html index 2cda0d1a6..9f20d329f 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs058.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs058.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs059.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs059.html index 02d92efc6..9093acc0b 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs059.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs059.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/._DecisionTrees-bs060.html b/doc/pub/DecisionTrees/html/._DecisionTrees-bs060.html index 5af631131..b63aec67f 100644 --- a/doc/pub/DecisionTrees/html/._DecisionTrees-bs060.html +++ b/doc/pub/DecisionTrees/html/._DecisionTrees-bs060.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • diff --git a/doc/pub/DecisionTrees/html/DecisionTrees-bs.html b/doc/pub/DecisionTrees/html/DecisionTrees-bs.html index 39a7c6c43..b1cd969e8 100644 --- a/doc/pub/DecisionTrees/html/DecisionTrees-bs.html +++ b/doc/pub/DecisionTrees/html/DecisionTrees-bs.html @@ -124,11 +124,11 @@ Automatically generated HTML file from DocOnce source 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -237,8 +237,8 @@ MathJax.Hub.Config({
  • Boosting, a Bird'e Eye
  • What is boosting? Additive Modelling/Iterative Fitting
  • Iterative Fitting, Regression and Squared-error Cost Function
  • -
  • Squared Error Exampe and Iterative Fitting
  • -
  • Iterative Fitting, Classification, AdaBoost
  • +
  • Squared-Error Example and Iterative Fitting
  • +
  • Iterative Fitting, Classification and AdaBoost
  • Adaptive Boosting, AdaBoost
  • Building up AdaBoost
  • Adaptive boosting: AdaBoost, Basic Algorithm
  • @@ -285,7 +285,7 @@ MathJax.Hub.Config({
    [2] Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University

    -

    Nov 10, 2019

    +

    Nov 11, 2019


    diff --git a/doc/pub/DecisionTrees/html/DecisionTrees-reveal.html b/doc/pub/DecisionTrees/html/DecisionTrees-reveal.html index 5c102282c..59ee06a8b 100644 --- a/doc/pub/DecisionTrees/html/DecisionTrees-reveal.html +++ b/doc/pub/DecisionTrees/html/DecisionTrees-reveal.html @@ -148,7 +148,7 @@ MathJax.Hub.Config({

    [2] Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University

     
    -

    Nov 10, 2019

    +

    Nov 11, 2019


    @@ -2051,7 +2051,7 @@ The way we proceed is as follows (here we specialize to the squared-error cost f

    1. minimize \( \sum_{i=0}^{n-1}(y_i-f_{m-1}(x_i)-\beta b(x;\gamma))^2 \) wrt \( \gamma \) and \( \beta \)
    2. -

    3. This gives the optimial values \( \beta_m \) and \( \gamma_m \)
    4. +

    5. This gives the optimal values \( \beta_m \) and \( \gamma_m \)
    6. Determine then the new values \( f_m(x)=f_{m-1}(x) +\beta_m b(x;\gamma_m) \)

    @@ -2065,7 +2065,7 @@ at the internal nodes, and the predictions at the terminal nodes.

    -

    Squared Error Exampe and Iterative Fitting

    +

    Squared-Error Example and Iterative Fitting

    To better understand what happens, let us develop the steps for the iterative fitting using the above squared error function. @@ -2074,7 +2074,7 @@ To better understand what happens, let us develop the steps for the iterative fi For simplicity we assume also that our functions \( b(x;\gamma)=1+\gamma x \).

    -This means that for every iteration, we need to optmize +This means that for every iteration, we need to optimize

     
    $$ @@ -2098,7 +2098,7 @@ $$ $$

     
    -We can then rewrite these equations as (defining \( w_i=1+\gamma x_i) \) +We can then rewrite these equations as (defining \( \boldsymbol{w}=\boldsymbol{e}+\gamma x_i) \) with \( \boldsymbol{e} \) being the unit vector)

     
    $$ \gamma \boldsymbol{w}^T(\boldsymbol{y}-\beta\gamma \boldsymbol{w})=0, @@ -2113,7 +2113,7 @@ $$

     

    -which leads \( \gamma =(\boldsymbol{x}^T\boldsymbol{y}-\beta\boldsymbol{x}^T\em{e})/(\beta\boldsymbol{x}^T\boldsymbol{x}) \). Inserting +which leads to \( \gamma =(\boldsymbol{x}^T\boldsymbol{y}-\beta\boldsymbol{x}^T\boldsymbol{e})/(\beta\boldsymbol{x}^T\boldsymbol{x}) \). Inserting for \( \beta \) gives us an equation for \( \gamma \).

    @@ -2123,7 +2123,7 @@ The solution to these two equations gives us in turn \( \beta_1 \) and \( \gamma

    -

    Iterative Fitting, Classification, AdaBoost

    +

    Iterative Fitting, Classification and AdaBoost

    Let us consider a binary classification problem with two outcomes \( y_i \in \{-1,1\} \) and \( i=0,1,2,\dots,n-1 \) as our set of @@ -2358,7 +2358,7 @@ plt.show()

    Gradient boosting: Basics

    -Gradient boosting is again a similar technique to Adapative boosting, +Gradient boosting is again a similar technique to Adaptive boosting, it combines so-called weak classifiers or regressors into a strong method via a series of iterations. diff --git a/doc/pub/DecisionTrees/html/DecisionTrees-solarized.html b/doc/pub/DecisionTrees/html/DecisionTrees-solarized.html index acfe40fa5..27309b5be 100644 --- a/doc/pub/DecisionTrees/html/DecisionTrees-solarized.html +++ b/doc/pub/DecisionTrees/html/DecisionTrees-solarized.html @@ -144,11 +144,11 @@ div { text-align: justify; text-justify: inter-word; } 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -214,7 +214,7 @@ MathJax.Hub.Config({

    [2] Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University

    -

    Nov 10, 2019

    +

    Nov 11, 2019












    @@ -2054,7 +2054,7 @@ The way we proceed is as follows (here we specialize to the squared-error cost f

    1. minimize \( \sum_{i=0}^{n-1}(y_i-f_{m-1}(x_i)-\beta b(x;\gamma))^2 \) wrt \( \gamma \) and \( \beta \)
    2. -
    3. This gives the optimial values \( \beta_m \) and \( \gamma_m \)
    4. +
    5. This gives the optimal values \( \beta_m \) and \( \gamma_m \)
    6. Determine then the new values \( f_m(x)=f_{m-1}(x) +\beta_m b(x;\gamma_m) \)
    @@ -2067,7 +2067,7 @@ at the internal nodes, and the predictions at the terminal nodes.











    -

    Squared Error Exampe and Iterative Fitting

    +

    Squared-Error Example and Iterative Fitting

    To better understand what happens, let us develop the steps for the iterative fitting using the above squared error function. @@ -2076,7 +2076,7 @@ To better understand what happens, let us develop the steps for the iterative fi For simplicity we assume also that our functions \( b(x;\gamma)=1+\gamma x \).

    -This means that for every iteration, we need to optmize +This means that for every iteration, we need to optimize $$ (\beta_m,\gamma_m) \mathrm{argmin}_{\beta,\lambda}\hspace{0.1cm} \sum_{i=0}^{n-1}(y_i-f_{m-1}(x_i)-\beta b(x;\gamma))^2=\sum_{i=0}^{n-1}(y_i-f_{m-1}(x_i)-\beta(1+\gamma x_i))^2. @@ -2094,7 +2094,7 @@ $$ \frac{\partial {\cal C}}{\partial \gamma} =-2\sum_{i}\beta x_i(y_i-\beta(1+\gamma x_i))=0. $$ -We can then rewrite these equations as (defining \( w_i=1+\gamma x_i) \) +We can then rewrite these equations as (defining \( \boldsymbol{w}=\boldsymbol{e}+\gamma x_i) \) with \( \boldsymbol{e} \) being the unit vector) $$ \gamma \boldsymbol{w}^T(\boldsymbol{y}-\beta\gamma \boldsymbol{w})=0, $$ @@ -2105,7 +2105,7 @@ $$ $$

    -which leads \( \gamma =(\boldsymbol{x}^T\boldsymbol{y}-\beta\boldsymbol{x}^T\em{e})/(\beta\boldsymbol{x}^T\boldsymbol{x}) \). Inserting +which leads to \( \gamma =(\boldsymbol{x}^T\boldsymbol{y}-\beta\boldsymbol{x}^T\boldsymbol{e})/(\beta\boldsymbol{x}^T\boldsymbol{x}) \). Inserting for \( \beta \) gives us an equation for \( \gamma \).

    @@ -2115,7 +2115,7 @@ The solution to these two equations gives us in turn \( \beta_1 \) and \( \gamma











    -

    Iterative Fitting, Classification, AdaBoost

    +

    Iterative Fitting, Classification and AdaBoost

    Let us consider a binary classification problem with two outcomes \( y_i \in \{-1,1\} \) and \( i=0,1,2,\dots,n-1 \) as our set of @@ -2319,7 +2319,7 @@ plt.show()

    Gradient boosting: Basics

    -Gradient boosting is again a similar technique to Adapative boosting, +Gradient boosting is again a similar technique to Adaptive boosting, it combines so-called weak classifiers or regressors into a strong method via a series of iterations. diff --git a/doc/pub/DecisionTrees/html/DecisionTrees.html b/doc/pub/DecisionTrees/html/DecisionTrees.html index 1c1b06da5..f596aab80 100644 --- a/doc/pub/DecisionTrees/html/DecisionTrees.html +++ b/doc/pub/DecisionTrees/html/DecisionTrees.html @@ -149,11 +149,11 @@ div { text-align: justify; text-justify: inter-word; } 2, None, '___sec46'), - ('Squared Error Exampe and Iterative Fitting', + ('Squared-Error Example and Iterative Fitting', 2, None, '___sec47'), - ('Iterative Fitting, Classification, AdaBoost', + ('Iterative Fitting, Classification and AdaBoost', 2, None, '___sec48'), @@ -219,7 +219,7 @@ MathJax.Hub.Config({

    [2] Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University

    -

    Nov 10, 2019

    +

    Nov 11, 2019












    @@ -2059,7 +2059,7 @@ The way we proceed is as follows (here we specialize to the squared-error cost f

    1. minimize \( \sum_{i=0}^{n-1}(y_i-f_{m-1}(x_i)-\beta b(x;\gamma))^2 \) wrt \( \gamma \) and \( \beta \)
    2. -
    3. This gives the optimial values \( \beta_m \) and \( \gamma_m \)
    4. +
    5. This gives the optimal values \( \beta_m \) and \( \gamma_m \)
    6. Determine then the new values \( f_m(x)=f_{m-1}(x) +\beta_m b(x;\gamma_m) \)
    @@ -2072,7 +2072,7 @@ at the internal nodes, and the predictions at the terminal nodes.











    -

    Squared Error Exampe and Iterative Fitting

    +

    Squared-Error Example and Iterative Fitting

    To better understand what happens, let us develop the steps for the iterative fitting using the above squared error function. @@ -2081,7 +2081,7 @@ To better understand what happens, let us develop the steps for the iterative fi For simplicity we assume also that our functions \( b(x;\gamma)=1+\gamma x \).

    -This means that for every iteration, we need to optmize +This means that for every iteration, we need to optimize $$ (\beta_m,\gamma_m) \mathrm{argmin}_{\beta,\lambda}\hspace{0.1cm} \sum_{i=0}^{n-1}(y_i-f_{m-1}(x_i)-\beta b(x;\gamma))^2=\sum_{i=0}^{n-1}(y_i-f_{m-1}(x_i)-\beta(1+\gamma x_i))^2. @@ -2099,7 +2099,7 @@ $$ \frac{\partial {\cal C}}{\partial \gamma} =-2\sum_{i}\beta x_i(y_i-\beta(1+\gamma x_i))=0. $$ -We can then rewrite these equations as (defining \( w_i=1+\gamma x_i) \) +We can then rewrite these equations as (defining \( \boldsymbol{w}=\boldsymbol{e}+\gamma x_i) \) with \( \boldsymbol{e} \) being the unit vector) $$ \gamma \boldsymbol{w}^T(\boldsymbol{y}-\beta\gamma \boldsymbol{w})=0, $$ @@ -2110,7 +2110,7 @@ $$ $$

    -which leads \( \gamma =(\boldsymbol{x}^T\boldsymbol{y}-\beta\boldsymbol{x}^T\em{e})/(\beta\boldsymbol{x}^T\boldsymbol{x}) \). Inserting +which leads to \( \gamma =(\boldsymbol{x}^T\boldsymbol{y}-\beta\boldsymbol{x}^T\boldsymbol{e})/(\beta\boldsymbol{x}^T\boldsymbol{x}) \). Inserting for \( \beta \) gives us an equation for \( \gamma \).

    @@ -2120,7 +2120,7 @@ The solution to these two equations gives us in turn \( \beta_1 \) and \( \gamma











    -

    Iterative Fitting, Classification, AdaBoost

    +

    Iterative Fitting, Classification and AdaBoost

    Let us consider a binary classification problem with two outcomes \( y_i \in \{-1,1\} \) and \( i=0,1,2,\dots,n-1 \) as our set of @@ -2324,7 +2324,7 @@ plt.show()

    Gradient boosting: Basics

    -Gradient boosting is again a similar technique to Adapative boosting, +Gradient boosting is again a similar technique to Adaptive boosting, it combines so-called weak classifiers or regressors into a strong method via a series of iterations. diff --git a/doc/pub/DecisionTrees/ipynb/DecisionTrees.ipynb b/doc/pub/DecisionTrees/ipynb/DecisionTrees.ipynb index a1baa3fae..4bfc45466 100644 --- a/doc/pub/DecisionTrees/ipynb/DecisionTrees.ipynb +++ b/doc/pub/DecisionTrees/ipynb/DecisionTrees.ipynb @@ -10,7 +10,7 @@ " \n", "**Morten Hjorth-Jensen**, Department of Physics, University of Oslo and Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University\n", "\n", - "Date: **Nov 10, 2019**\n", + "Date: **Nov 11, 2019**\n", "\n", "Copyright 1999-2019, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license\n", "\n", @@ -2107,7 +2107,7 @@ "\n", "a. minimize $\\sum_{i=0}^{n-1}(y_i-f_{m-1}(x_i)-\\beta b(x;\\gamma))^2$ wrt $\\gamma$ and $\\beta$\n", "\n", - "b. This gives the optimial values $\\beta_m$ and $\\gamma_m$\n", + "b. This gives the optimal values $\\beta_m$ and $\\gamma_m$\n", "\n", "c. Determine then the new values $f_m(x)=f_{m-1}(x) +\\beta_m b(x;\\gamma_m)$\n", "\n", @@ -2117,13 +2117,13 @@ "at the internal nodes, and the predictions at the terminal nodes.\n", "\n", "\n", - "## Squared Error Exampe and Iterative Fitting\n", + "## Squared-Error Example and Iterative Fitting\n", "\n", "To better understand what happens, let us develop the steps for the iterative fitting using the above squared error function.\n", "\n", "For simplicity we assume also that our functions $b(x;\\gamma)=1+\\gamma x$. \n", "\n", - "This means that for every iteration, we need to optmize" + "This means that for every iteration, we need to optimize" ] }, { @@ -2172,7 +2172,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We can then rewrite these equations as (defining $w_i=1+\\gamma x_i)$" + "We can then rewrite these equations as (defining $\\boldsymbol{w}=\\boldsymbol{e}+\\gamma x_i)$ with $\\boldsymbol{e}$ being the unit vector)" ] }, { @@ -2204,7 +2204,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "which leads $\\gamma =(\\boldsymbol{x}^T\\boldsymbol{y}-\\beta\\boldsymbol{x}^T\\em{e})/(\\beta\\boldsymbol{x}^T\\boldsymbol{x})$. Inserting\n", + "which leads to $\\gamma =(\\boldsymbol{x}^T\\boldsymbol{y}-\\beta\\boldsymbol{x}^T\\boldsymbol{e})/(\\beta\\boldsymbol{x}^T\\boldsymbol{x})$. Inserting\n", "for $\\beta$ gives us an equation for $\\gamma$.\n", "\n", "The solution to these two equations gives us in turn $\\beta_1$ and $\\gamma_1$ leading to the new expression for $f_1(x)$ as\n", @@ -2212,7 +2212,7 @@ "\n", "\n", "\n", - "## Iterative Fitting, Classification, AdaBoost\n", + "## Iterative Fitting, Classification and AdaBoost\n", "\n", "Let us consider a binary classification problem with two outcomes $y_i \\in \\{-1,1\\}$ and $i=0,1,2,\\dots,n-1$ as our set of\n", "observations. We define a classification function $G(x)$ which produces a prediction taking any of the two values \n", @@ -2557,7 +2557,7 @@ "source": [ "## Gradient boosting: Basics\n", "\n", - "Gradient boosting is again a similar technique to Adapative boosting,\n", + "Gradient boosting is again a similar technique to Adaptive boosting,\n", "it combines so-called weak classifiers or regressors into a strong\n", "method via a series of iterations.\n", "\n", diff --git a/doc/pub/DecisionTrees/ipynb/ipynb-DecisionTrees-src.tar.gz b/doc/pub/DecisionTrees/ipynb/ipynb-DecisionTrees-src.tar.gz index 2a8f44d75..c31a23f48 100644 Binary files a/doc/pub/DecisionTrees/ipynb/ipynb-DecisionTrees-src.tar.gz and b/doc/pub/DecisionTrees/ipynb/ipynb-DecisionTrees-src.tar.gz differ diff --git a/doc/pub/DecisionTrees/pdf/DecisionTrees-minted.pdf b/doc/pub/DecisionTrees/pdf/DecisionTrees-minted.pdf index bfe73b849..93861c875 100644 Binary files a/doc/pub/DecisionTrees/pdf/DecisionTrees-minted.pdf and b/doc/pub/DecisionTrees/pdf/DecisionTrees-minted.pdf differ diff --git a/doc/src/DecisionTrees/DecisionTrees.do.txt b/doc/src/DecisionTrees/DecisionTrees.do.txt index 583e64200..1f829c9ec 100644 --- a/doc/src/DecisionTrees/DecisionTrees.do.txt +++ b/doc/src/DecisionTrees/DecisionTrees.do.txt @@ -1691,7 +1691,7 @@ o Establish a cost function, here ${\cal C}(\bm{y},\bm{f}) = \frac{1}{n} \sum_{i o Initialize with a guess $f_0(x)$. It could be one or even zero or some random numbers. o For $m=1:M$ o minimize $\sum_{i=0}^{n-1}(y_i-f_{m-1}(x_i)-\beta b(x;\gamma))^2$ wrt $\gamma$ and $\beta$ - o This gives the optimial values $\beta_m$ and $\gamma_m$ + o This gives the optimal values $\beta_m$ and $\gamma_m$ o Determine then the new values $f_m(x)=f_{m-1}(x) +\beta_m b(x;\gamma_m)$ We could use any of the algorithms we have discussed till now. If we @@ -1700,13 +1700,13 @@ at the internal nodes, and the predictions at the terminal nodes. !split -===== Squared Error Exampe and Iterative Fitting ===== +===== Squared-Error Example and Iterative Fitting ===== To better understand what happens, let us develop the steps for the iterative fitting using the above squared error function. For simplicity we assume also that our functions $b(x;\gamma)=1+\gamma x$. -This means that for every iteration, we need to optmize +This means that for every iteration, we need to optimize !bt \[ @@ -1727,7 +1727,7 @@ and \frac{\partial {\cal C}}{\partial \gamma} =-2\sum_{i}\beta x_i(y_i-\beta(1+\gamma x_i))=0. \] !et -We can then rewrite these equations as (defining $w_i=1+\gamma x_i)$ +We can then rewrite these equations as (defining $\bm{w}=\bm{e}+\gamma x_i)$ with $\bm{e}$ being the unit vector) !bt \[ \gamma \bm{w}^T(\bm{y}-\beta\gamma \bm{w})=0, @@ -1740,7 +1740,7 @@ which gives us $\beta = \bm{w}^T\bm{y}/(\bm{w}^T\bm{w})$. Similarly we have \] !et -which leads $\gamma =(\bm{x}^T\bm{y}-\beta\bm{x}^T\em{e})/(\beta\bm{x}^T\bm{x})$. Inserting +which leads to $\gamma =(\bm{x}^T\bm{y}-\beta\bm{x}^T\bm{e})/(\beta\bm{x}^T\bm{x})$. Inserting for $\beta$ gives us an equation for $\gamma$. The solution to these two equations gives us in turn $\beta_1$ and $\gamma_1$ leading to the new expression for $f_1(x)$ as @@ -1749,7 +1749,7 @@ $f_1(x) = \beta_1(1+\gamma_1x)$. Doing this $M$ times results in our final estim !split -===== Iterative Fitting, Classification, AdaBoost ===== +===== Iterative Fitting, Classification and AdaBoost ===== Let us consider a binary classification problem with two outcomes $y_i \in \{-1,1\}$ and $i=0,1,2,\dots,n-1$ as our set of observations. We define a classification function $G(x)$ which produces a prediction taking any of the two values @@ -1940,7 +1940,7 @@ plt.show() !split ===== Gradient boosting: Basics ===== -Gradient boosting is again a similar technique to Adapative boosting, +Gradient boosting is again a similar technique to Adaptive boosting, it combines so-called weak classifiers or regressors into a strong method via a series of iterations.