From b6ddcba9c19c19e5ed0911f8966c49da63548c1c Mon Sep 17 00:00:00 2001
From: Morten Hjorth-Jensen <morten.hjorth-jensen@fys.uio.no>
Date: Thu, 23 Nov 2023 15:37:32 +0100
Subject: [PATCH] update

---
 doc/pub/week47/html/._week47-bs001.html      |    2 +
 doc/pub/week47/html/week47-reveal.html       |    4 +
 doc/pub/week47/html/week47-solarized.html    |    2 +
 doc/pub/week47/html/week47.html              |    2 +
 doc/pub/week47/ipynb/ipynb-week47-src.tar.gz |  Bin 823750 -> 823750 bytes
 doc/pub/week47/ipynb/week47.ipynb            | 1268 +++++++++---------
 doc/src/week47/week47.do.txt                 |    2 +
 7 files changed, 678 insertions(+), 602 deletions(-)

diff --git a/doc/pub/week47/html/._week47-bs001.html b/doc/pub/week47/html/._week47-bs001.html
index e255492d4..fa2c1efaf 100644
--- a/doc/pub/week47/html/._week47-bs001.html
+++ b/doc/pub/week47/html/._week47-bs001.html
@@ -406,6 +406,8 @@ MathJax.Hub.Config({
   <li> Readings and Videos:</li>
 <ul>
     <li> These lecture notes</li>
+    <li> <a href="https://youtu.be/SpWXsvn5I9E" target="_self">Video of Lecture</a></li>
+    <li> <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesNov23.pdf" target="_self">Whiteboard notes</a></li>
     <li> <a href="https://www.youtube.com/watch?v=RmajweUFKvM&ab_channel=Simplilearn" target="_self">Video on Decision trees</a></li>
     <li> <a href="https://www.youtube.com/watch?v=wPqtzj5VZus&ab_channel=H2O.ai" target="_self">Video on boosting methods by Hastie</a></li>
     <li> <a href="https://www.youtube.com/watch?v=LsK-xG1cLYA" target="_self">Video on AdaBoost</a></li>
diff --git a/doc/pub/week47/html/week47-reveal.html b/doc/pub/week47/html/week47-reveal.html
index 7375e92a5..4b92bfd42 100644
--- a/doc/pub/week47/html/week47-reveal.html
+++ b/doc/pub/week47/html/week47-reveal.html
@@ -221,6 +221,10 @@ MathJax.Hub.Config({
 
 <p><li> These lecture notes</li>
 
+<p><li> <a href="https://youtu.be/SpWXsvn5I9E" target="_blank">Video of Lecture</a></li>
+
+<p><li> <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesNov23.pdf" target="_blank">Whiteboard notes</a></li>
+
 <p><li> <a href="https://www.youtube.com/watch?v=RmajweUFKvM&ab_channel=Simplilearn" target="_blank">Video on Decision trees</a></li>
 
 <p><li> <a href="https://www.youtube.com/watch?v=wPqtzj5VZus&ab_channel=H2O.ai" target="_blank">Video on boosting methods by Hastie</a></li>
diff --git a/doc/pub/week47/html/week47-solarized.html b/doc/pub/week47/html/week47-solarized.html
index 04261e4a7..2d6838ca8 100644
--- a/doc/pub/week47/html/week47-solarized.html
+++ b/doc/pub/week47/html/week47-solarized.html
@@ -350,6 +350,8 @@ MathJax.Hub.Config({
   <li> Readings and Videos:</li>
 <ul>
     <li> These lecture notes</li>
+    <li> <a href="https://youtu.be/SpWXsvn5I9E" target="_blank">Video of Lecture</a></li>
+    <li> <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesNov23.pdf" target="_blank">Whiteboard notes</a></li>
     <li> <a href="https://www.youtube.com/watch?v=RmajweUFKvM&ab_channel=Simplilearn" target="_blank">Video on Decision trees</a></li>
     <li> <a href="https://www.youtube.com/watch?v=wPqtzj5VZus&ab_channel=H2O.ai" target="_blank">Video on boosting methods by Hastie</a></li>
     <li> <a href="https://www.youtube.com/watch?v=LsK-xG1cLYA" target="_blank">Video on AdaBoost</a></li>
diff --git a/doc/pub/week47/html/week47.html b/doc/pub/week47/html/week47.html
index c2717ae1a..b03f26452 100644
--- a/doc/pub/week47/html/week47.html
+++ b/doc/pub/week47/html/week47.html
@@ -427,6 +427,8 @@ MathJax.Hub.Config({
   <li> Readings and Videos:</li>
 <ul>
     <li> These lecture notes</li>
+    <li> <a href="https://youtu.be/SpWXsvn5I9E" target="_blank">Video of Lecture</a></li>
+    <li> <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesNov23.pdf" target="_blank">Whiteboard notes</a></li>
     <li> <a href="https://www.youtube.com/watch?v=RmajweUFKvM&ab_channel=Simplilearn" target="_blank">Video on Decision trees</a></li>
     <li> <a href="https://www.youtube.com/watch?v=wPqtzj5VZus&ab_channel=H2O.ai" target="_blank">Video on boosting methods by Hastie</a></li>
     <li> <a href="https://www.youtube.com/watch?v=LsK-xG1cLYA" target="_blank">Video on AdaBoost</a></li>
diff --git a/doc/pub/week47/ipynb/ipynb-week47-src.tar.gz b/doc/pub/week47/ipynb/ipynb-week47-src.tar.gz
index f1d1b4b31a631125fab00b88e58b543cd0f866c3..c23d0e58c902a8809d78ef77a4b731b9a2eac564 100644
GIT binary patch
delta 53
zcmX@M*yz||BR2VN4u;vujcl!KjIC@;t!&J#Y%Hy8tgUQ75%yL#j#f6#RyM9yHtwx#
IJO?HM0F`_V#{d8T

delta 53
zcmX@M*yz||BR2VN4u*L4Mz&Tq##T0_RyO8VHkMX4)>by42zx6VM=Kj=D;rlU8~0W=
Ho&ysBeCQ1?

diff --git a/doc/pub/week47/ipynb/week47.ipynb b/doc/pub/week47/ipynb/week47.ipynb
index a26e9bb0c..06576e777 100644
--- a/doc/pub/week47/ipynb/week47.ipynb
+++ b/doc/pub/week47/ipynb/week47.ipynb
@@ -2,8 +2,10 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "795eb464",
-   "metadata": {},
+   "id": "6314bf67",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "<!-- HTML file automatically generated from DocOnce source (https://github.com/doconce/doconce/)\n",
     "doconce format html week47.do.txt --no_mako -->\n",
@@ -12,8 +14,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d1aa4009",
-   "metadata": {},
+   "id": "c46d28d1",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "# Week 47: From Decision Trees to Ensemble Methods, Random Forests and Boosting Methods   and Summary of Course\n",
     "**Morten Hjorth-Jensen**, Department of Physics, University of Oslo and Department of Physics and Astronomy and Facility for Rare Ion Beams, Michigan State University\n",
@@ -23,8 +27,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cb6aa61c",
-   "metadata": {},
+   "id": "091c41a2",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Plan for week 47\n",
     "\n",
@@ -44,6 +50,10 @@
     "\n",
     "    * These lecture notes\n",
     "\n",
+    "    * [Video of Lecture](https://youtu.be/SpWXsvn5I9E)\n",
+    "\n",
+    "    * [Whiteboard notes](https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesNov23.pdf)\n",
+    "\n",
     "    * [Video on Decision trees](https://www.youtube.com/watch?v=RmajweUFKvM&ab_channel=Simplilearn)\n",
     "\n",
     "    * [Video on boosting methods by Hastie](https://www.youtube.com/watch?v=wPqtzj5VZus&ab_channel=H2O.ai)\n",
@@ -57,8 +67,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "15ea90a2",
-   "metadata": {},
+   "id": "3f081cea",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Bagging\n",
     "\n",
@@ -77,8 +89,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9fa05123",
-   "metadata": {},
+   "id": "3789d0ad",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## More bagging\n",
     "\n",
@@ -107,8 +121,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ee547e51",
-   "metadata": {},
+   "id": "b6bfb9a8",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Making your own Bootstrap: Changing the Level of the Decision Tree\n",
     "\n",
@@ -119,62 +135,12 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "c5508f3e",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Polynomial degree: 1\n",
-      "Error: 0.0833546300081958\n",
-      "Bias^2: 0.072667398423759\n",
-      "Var: 0.010687231584436805\n",
-      "0.0833546300081958 >= 0.072667398423759 + 0.010687231584436805 = 0.0833546300081958\n",
-      "Polynomial degree: 2\n",
-      "Error: 0.05330562750186478\n",
-      "Bias^2: 0.04400019242745484\n",
-      "Var: 0.009305435074409906\n",
-      "0.05330562750186478 >= 0.04400019242745484 + 0.009305435074409906 = 0.05330562750186475\n",
-      "Polynomial degree: 3\n",
-      "Error: 0.029380745484863514\n",
-      "Bias^2: 0.021359335848078257\n",
-      "Var: 0.00802140963678523\n",
-      "0.029380745484863514 >= 0.021359335848078257 + 0.00802140963678523 = 0.02938074548486349\n",
-      "Polynomial degree: 4\n",
-      "Error: 0.023174561372167397\n",
-      "Bias^2: 0.017443737060686214\n",
-      "Var: 0.0057308243114812\n",
-      "0.023174561372167397 >= 0.017443737060686214 + 0.0057308243114812 = 0.023174561372167415\n",
-      "Polynomial degree: 5\n",
-      "Error: 0.02379591911089059\n",
-      "Bias^2: 0.017007639979909707\n",
-      "Var: 0.006788279130980878\n",
-      "0.02379591911089059 >= 0.017007639979909707 + 0.006788279130980878 = 0.023795919110890587\n",
-      "Polynomial degree: 6\n",
-      "Error: 0.025448637375892\n",
-      "Bias^2: 0.018631497505243337\n",
-      "Var: 0.0068171398706486554\n",
-      "0.025448637375892 >= 0.018631497505243337 + 0.0068171398706486554 = 0.025448637375891994\n",
-      "Polynomial degree: 7\n",
-      "Error: 0.026846018436808162\n",
-      "Bias^2: 0.019049418403031867\n",
-      "Var: 0.00779660003377629\n",
-      "0.026846018436808162 >= 0.019049418403031867 + 0.00779660003377629 = 0.02684601843680816\n",
-      "Simple tree: 0.5756660326095742\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "id": "bd257c56",
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
+   "outputs": [],
    "source": [
     "%matplotlib inline\n",
     "\n",
@@ -271,8 +237,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a5e9cd81",
-   "metadata": {},
+   "id": "ec697394",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Random forests\n",
     "\n",
@@ -292,8 +260,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fd4f2752",
-   "metadata": {},
+   "id": "2f8e4054",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "m\\approx \\sqrt{p}.\n",
@@ -302,8 +272,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "faa2b01b",
-   "metadata": {},
+   "id": "5476fc65",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "In building a random forest, at\n",
     "each split in the tree, the algorithm is not even allowed to consider\n",
@@ -325,8 +297,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0c04c2a3",
-   "metadata": {},
+   "id": "024d17cc",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Random Forest Algorithm\n",
     "The algorithm described here can be applied to both classification and regression problems.\n",
@@ -349,8 +323,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "11833662",
-   "metadata": {},
+   "id": "adbab589",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Random Forests Compared with other Methods on the Cancer Data"
    ]
@@ -358,54 +334,12 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "d0ddbeee",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "(426, 30)\n",
-      "(143, 30)\n",
-      "Test set accuracy Logistic Regression with scaled data: 0.96\n",
-      "Test set accuracy SVM with scaled data: 0.96\n",
-      "Test set accuracy with Decision Trees and scaled data: 0.88\n",
-      "[0.93333333 0.8        0.93333333 1.         1.         0.92857143\n",
-      " 1.         0.92857143 0.92857143 1.        ]\n",
-      "Test set accuracy with Random Forests and scaled data: 0.98\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "id": "44d47f87",
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
+   "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
@@ -472,8 +406,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d8f43bda",
-   "metadata": {},
+   "id": "2670f5de",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "Recall that the cumulative gains curve shows the percentage of the\n",
     "overall number of cases in a given category *gained* by targeting a\n",
@@ -486,8 +422,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "95aee084",
-   "metadata": {},
+   "id": "622c79ae",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Compare  Bagging on Trees with Random Forests"
    ]
@@ -495,8 +433,11 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "316f2b3a",
-   "metadata": {},
+   "id": "eceba36c",
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "bag_clf = BaggingClassifier(\n",
@@ -507,20 +448,12 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "e41da901",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.9790209790209791"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "id": "40d42e1a",
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
+   "outputs": [],
    "source": [
     "bag_clf.fit(X_train, y_train)\n",
     "y_pred = bag_clf.predict(X_test)\n",
@@ -533,8 +466,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b1ded974",
-   "metadata": {},
+   "id": "bee77377",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Boosting, a Bird's Eye View\n",
     "\n",
@@ -551,8 +486,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5c4a65da",
-   "metadata": {},
+   "id": "4ea2d5e4",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## What is boosting? Additive Modelling/Iterative Fitting\n",
     "\n",
@@ -563,8 +500,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "995a1a54",
-   "metadata": {},
+   "id": "c69bf1b6",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "f_M(x) = \\sum_{i=1}^M \\beta_m b(x;\\gamma_m),\n",
@@ -573,8 +512,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a6dea1ae",
-   "metadata": {},
+   "id": "d53b6cb2",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "where $\\beta_m$ are the expansion parameters to be determined in a\n",
     "minimization process and $b(x;\\gamma_m)$ are some simple functions of\n",
@@ -588,8 +529,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "282afb01",
-   "metadata": {},
+   "id": "57ee288e",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "\\sigma(t) = \\frac{1}{1+\\exp{(-t)}},\n",
@@ -598,8 +541,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f9e28966",
-   "metadata": {},
+   "id": "d03b9aa0",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "where $t=\\gamma_0+\\gamma_1 x$ and the parameters $\\gamma_0$ and\n",
     "$\\gamma_1$ were determined by the Logistic Regression fitting\n",
@@ -610,8 +555,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fd88cd38",
-   "metadata": {},
+   "id": "3caace0f",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "C(\\boldsymbol{y},\\boldsymbol{f}) = \\frac{1}{n} \\sum_{i=0}^{n-1}(y_i-f(x_i))^2.\n",
@@ -620,8 +567,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "20750851",
-   "metadata": {},
+   "id": "99c4d861",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "In this case the function $f(x)$ was replaced by the design matrix\n",
     "$\\boldsymbol{X}$ and the unknown linear regression parameters $\\boldsymbol{\\beta}$,\n",
@@ -631,8 +580,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6784d540",
-   "metadata": {},
+   "id": "15e7309c",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "\\boldsymbol{\\beta}=\\left(\\boldsymbol{X}^T\\boldsymbol{X}\\right)^{-1}\\boldsymbol{X}^T\\boldsymbol{y}.\n",
@@ -641,16 +592,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "527c0cec",
-   "metadata": {},
+   "id": "78f883b0",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "In iterative fitting or additive modeling, we minimize the cost function with respect to the parameters $\\beta_m$ and $\\gamma_m$."
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "72ca9006",
-   "metadata": {},
+   "id": "95d67f7e",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Iterative Fitting, Regression and Squared-error Cost Function\n",
     "\n",
@@ -675,8 +630,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5a4f92a1",
-   "metadata": {},
+   "id": "571085d4",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Squared-Error Example and Iterative Fitting\n",
     "\n",
@@ -689,8 +646,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "92a7334d",
-   "metadata": {},
+   "id": "6c23e842",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "(\\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.\n",
@@ -699,8 +658,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c72f3a5b",
-   "metadata": {},
+   "id": "6a3315ef",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "We start our iteration by simply setting $f_0(x)=0$. \n",
     "Taking the derivatives  with respect to $\\beta$ and $\\gamma$ we obtain"
@@ -708,8 +669,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c42f68c9",
-   "metadata": {},
+   "id": "c377e717",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "\\frac{\\partial {\\cal C}}{\\partial \\beta} = -2\\sum_{i}(1+\\gamma x_i)(y_i-\\beta(1+\\gamma x_i))=0,\n",
@@ -718,16 +681,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0daa461a",
-   "metadata": {},
+   "id": "0effec3c",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "and"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "1854b53d",
-   "metadata": {},
+   "id": "5104bdd4",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "\\frac{\\partial {\\cal C}}{\\partial \\gamma} =-2\\sum_{i}\\beta x_i(y_i-\\beta(1+\\gamma x_i))=0.\n",
@@ -736,16 +703,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6ac1a90f",
-   "metadata": {},
+   "id": "07255d2b",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "We can then rewrite these equations as (defining $\\boldsymbol{w}=\\boldsymbol{e}+\\gamma \\boldsymbol{x})$ with $\\boldsymbol{e}$ being the unit vector)"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "818f12cd",
-   "metadata": {},
+   "id": "e597dcd5",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "\\gamma \\boldsymbol{w}^T(\\boldsymbol{y}-\\beta\\gamma \\boldsymbol{w})=0,\n",
@@ -754,16 +725,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6a804e62",
-   "metadata": {},
+   "id": "5044ba81",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "which gives us $\\beta = \\boldsymbol{w}^T\\boldsymbol{y}/(\\boldsymbol{w}^T\\boldsymbol{w})$. Similarly we have"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "30832ada",
-   "metadata": {},
+   "id": "6ec9b996",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "\\beta\\gamma \\boldsymbol{x}^T(\\boldsymbol{y}-\\beta(1+\\gamma \\boldsymbol{x}))=0,\n",
@@ -772,8 +747,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1c322106",
-   "metadata": {},
+   "id": "f6835c6d",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "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 $\\gamma$. This is a non-linear equation in the unknown $\\gamma$ and has to be solved numerically. \n",
@@ -784,8 +761,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ed6606f1",
-   "metadata": {},
+   "id": "ec4ec69c",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Iterative Fitting, Classification and AdaBoost\n",
     "\n",
@@ -798,8 +777,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "42da8542",
-   "metadata": {},
+   "id": "ee339678",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "\\mathrm{\\overline{err}}=\\frac{1}{n} \\sum_{i=0}^{n-1} I(y_i\\ne G(x_i)).\n",
@@ -808,8 +789,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "eed02e71",
-   "metadata": {},
+   "id": "e8eaad5d",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "The iterative procedure starts with defining a weak classifier whose\n",
     "error rate is barely better than random guessing.  The iterative\n",
@@ -822,8 +805,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f3705e28",
-   "metadata": {},
+   "id": "b401d599",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "f_M(x) = \\sum_{i=1}^M \\beta_m b(x;\\gamma_m),\n",
@@ -832,16 +817,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6999a946",
-   "metadata": {},
+   "id": "a9e7822e",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "will be a function of"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "0dab1427",
-   "metadata": {},
+   "id": "715194ce",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "G_M(x) = \\mathrm{sign} \\sum_{i=1}^M \\alpha_m G_m(x).\n",
@@ -850,8 +839,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "853e5217",
-   "metadata": {},
+   "id": "195fc1da",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Adaptive Boosting, AdaBoost\n",
     "\n",
@@ -860,8 +851,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "914fb6c3",
-   "metadata": {},
+   "id": "9436883a",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "f_m(x) = f_{m-1}(x)+\\beta_mG_m(x).\n",
@@ -870,8 +863,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9295ad53",
-   "metadata": {},
+   "id": "4ebf9f1e",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "The simplest possible cost function which leads (also simple from a computational point of view) to the AdaBoost algorithm is the\n",
     "exponential cost/loss function defined as"
@@ -879,8 +874,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7792adf2",
-   "metadata": {},
+   "id": "603422c9",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "C(\\boldsymbol{y},\\boldsymbol{f}) = \\sum_{i=0}^{n-1}\\exp{(-y_i(f_{m-1}(x_i)+\\beta G(x_i))}.\n",
@@ -889,8 +886,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "85796389",
-   "metadata": {},
+   "id": "da3e2e12",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "We optimize $\\beta$ and $G$ for each value of $m=1:M$ as we did in the regression case.\n",
     "This is normally done in two steps. Let us however first rewrite the cost function as"
@@ -898,8 +897,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0aba09b9",
-   "metadata": {},
+   "id": "851833f0",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "C(\\boldsymbol{y},\\boldsymbol{f}) = \\sum_{i=0}^{n-1}w_i^{m}\\exp{(-y_i\\beta G(x_i))},\n",
@@ -908,16 +909,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "45665b82",
-   "metadata": {},
+   "id": "4bbf5443",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "where we have defined $w_i^m= \\exp{(-y_if_{m-1}(x_i))}$."
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "410d49c5",
-   "metadata": {},
+   "id": "b63b18c5",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Building up AdaBoost\n",
     "\n",
@@ -926,8 +931,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "88a5b55d",
-   "metadata": {},
+   "id": "f3f75de8",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "G_m(x) = \\mathrm{sign} \\sum_{i=0}^{n-1} w_i^m I(y_i \\ne G_(x_i)),\n",
@@ -936,8 +943,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0b8dc34b",
-   "metadata": {},
+   "id": "998b02e8",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "which is the classifier that minimizes the weighted error rate in predicting $y$.\n",
     "\n",
@@ -946,8 +955,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "816375ba",
-   "metadata": {},
+   "id": "98b1751b",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "\\exp{-(\\beta)}\\sum_{y_i=G(x_i)}w_i^m+\\exp{(\\beta)}\\sum_{y_i\\ne G(x_i)}w_i^m,\n",
@@ -956,16 +967,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "69076d6e",
-   "metadata": {},
+   "id": "4b030d99",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "which can be rewritten as"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "3193c701",
-   "metadata": {},
+   "id": "e286c8e8",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "(\\exp{(\\beta)}-\\exp{-(\\beta)})\\sum_{i=0}^{n-1}w_i^mI(y_i\\ne G(x_i))+\\exp{(-\\beta)}\\sum_{i=0}^{n-1}w_i^m=0,\n",
@@ -974,16 +989,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "196dbc75",
-   "metadata": {},
+   "id": "7328b345",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "which leads to"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "5e0ddaf3",
-   "metadata": {},
+   "id": "b10d1b97",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "\\beta_m = \\frac{1}{2}\\log{\\frac{1-\\mathrm{\\overline{err}}}{\\mathrm{\\overline{err}}}},\n",
@@ -992,16 +1011,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "513a1032",
-   "metadata": {},
+   "id": "6601235f",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "where we have redefined the error as"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "a6c61596",
-   "metadata": {},
+   "id": "2d7d9eb9",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "\\mathrm{\\overline{err}}_m=\\frac{1}{n}\\frac{\\sum_{i=0}^{n-1}w_i^mI(y_i\\ne G(x_i)}{\\sum_{i=0}^{n-1}w_i^m},\n",
@@ -1010,16 +1033,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fe4ecc1d",
-   "metadata": {},
+   "id": "41a404a6",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "which leads to an update of"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "886aa5c4",
-   "metadata": {},
+   "id": "65f30690",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "f_m(x) = f_{m-1}(x) +\\beta_m G_m(x).\n",
@@ -1028,16 +1055,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "30de8eb6",
-   "metadata": {},
+   "id": "aea33aa2",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "This leads to the new weights"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "5d2444a5",
-   "metadata": {},
+   "id": "225e3f3e",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "w_i^{m+1} = w_i^m \\exp{(-y_i\\beta_m G_m(x_i))}\n",
@@ -1046,8 +1077,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "98f24f3b",
-   "metadata": {},
+   "id": "eb9cd9ea",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Adaptive boosting: AdaBoost, Basic Algorithm\n",
     "\n",
@@ -1064,8 +1097,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "957b82ca",
-   "metadata": {},
+   "id": "09491585",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "\\mathrm{err}=\\frac{1}{n}\\sum_{i=0}^{n-1}I(y_i\\ne G(x_i)),\n",
@@ -1074,16 +1109,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6306e903",
-   "metadata": {},
+   "id": "60b25717",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "where the function $I()$ is one if we misclassify and zero if we classify correctly."
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "85af08d8",
-   "metadata": {},
+   "id": "af1b7fce",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Basic Steps of AdaBoost\n",
     "\n",
@@ -1096,8 +1135,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5050dacd",
-   "metadata": {},
+   "id": "e207bb04",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "\\mathrm{\\overline{err}}_m=\\frac{\\sum_{i=0}^{n-1}w_i^m I(y_i\\ne G(x_i))}{\\sum_{i=0}^{n-1}w_i},\n",
@@ -1106,8 +1147,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "59ce2a92",
-   "metadata": {},
+   "id": "50ea5302",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "1. Then we start looping over all attempts at classifying, namely we start an iterative process for $m=1:M$, where $M$ is the final number of classifications. Our given classifier could for example be a plain decision tree.\n",
     "\n",
@@ -1132,8 +1175,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "89b2a0c9",
-   "metadata": {},
+   "id": "e6b2e841",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## AdaBoost Examples\n",
     "\n",
@@ -1143,40 +1188,12 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "1ca70ef7",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "id": "f3473567",
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
+   "outputs": [],
    "source": [
     "from sklearn.ensemble import AdaBoostClassifier\n",
     "\n",
@@ -1196,8 +1213,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "83276b45",
-   "metadata": {},
+   "id": "4bf435d0",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Gradient boosting: Basics with Steepest Descent/Functional Gradient Descent\n",
     "\n",
@@ -1212,8 +1231,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5c24b4fb",
-   "metadata": {},
+   "id": "6f9bf84b",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## The Squared-Error again! Steepest Descent\n",
     "\n",
@@ -1223,8 +1244,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5cb2e10f",
-   "metadata": {},
+   "id": "bceb5dce",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "(\\hat{\\boldsymbol{f}}) = \\mathrm{argmin}_{\\boldsymbol{f}}\\hspace{0.1cm} \\sum_{i=0}^{n-1}(y_i-f(x_i))^2.\n",
@@ -1233,16 +1256,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8d724d97",
-   "metadata": {},
+   "id": "b334a5df",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "We define a real function $h_m(x)$ that defines our final function $f_M(x)$ as"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "ef663ab7",
-   "metadata": {},
+   "id": "df096d69",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "f_M(x) = \\sum_{m=0}^M h_m(x).\n",
@@ -1251,16 +1278,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "59563e7b",
-   "metadata": {},
+   "id": "f0367c24",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "In the steepest decent approach we approximate $h_m(x) = -\\rho_m g_m(x)$, where $\\rho_m$ is a scalar and $g_m(x)$ the gradient defined as"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "d403d923",
-   "metadata": {},
+   "id": "7e83582e",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "g_m(x_i) = \\left[ \\frac{\\partial {\\cal L}(y_i, f(x_i))}{\\partial f(x_i)}\\right]_{f(x_i)=f_{m-1}(x_i)}.\n",
@@ -1269,8 +1300,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ab73f66a",
-   "metadata": {},
+   "id": "6b43e044",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "With the new gradient we can update $f_m(x) = f_{m-1}(x) -\\rho_m g_m(x)$. Using the above squared-error function we see that\n",
     "the gradient is $g_m(x_i) = -2(y_i-f(x_i))$.\n",
@@ -1280,8 +1313,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "761088a5",
-   "metadata": {},
+   "id": "5e5567eb",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "(\\rho_1) = \\mathrm{argmin}_{\\rho}\\hspace{0.1cm} \\sum_{i=0}^{n-1}(y_i+2\\rho y_i)^2.\n",
@@ -1290,8 +1325,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "21465bc1",
-   "metadata": {},
+   "id": "bc4464a3",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Steepest Descent Example\n",
     "\n",
@@ -1300,8 +1337,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5d786e53",
-   "metadata": {},
+   "id": "74a990d2",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "f_1(x) = f_{0}(x) -\\rho_1 g_1(x)=-y_i.\n",
@@ -1310,16 +1349,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cf342d8e",
-   "metadata": {},
+   "id": "11ac33af",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "We can then proceed and compute"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "0ffecaac",
-   "metadata": {},
+   "id": "31fad8d3",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "g_2(x_i) = \\left[ \\frac{\\partial {\\cal L}(y_i, f(x_i))}{\\partial f(x_i)}\\right]_{f(x_i)=f_{1}(x_i)=y_i}=-4y_i,\n",
@@ -1328,16 +1371,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "82234c63",
-   "metadata": {},
+   "id": "664e354f",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "and find a new value for $\\rho_2=-1/2$ and continue till we have reached $m=M$. We can modify the steepest descent method, or steepest boosting, by introducing what is called **gradient boosting**."
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "d886e0d6",
-   "metadata": {},
+   "id": "bdcc9bb0",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Gradient Boosting, algorithm\n",
     "\n",
@@ -1350,8 +1397,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3bc6ddc2",
-   "metadata": {},
+   "id": "91ea379e",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "C(\\boldsymbol{y},\\boldsymbol{f})=\\sum_{i=0}^{n-1}(y_i-f(x_i))^2.\n",
@@ -1360,8 +1409,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b6fdff99",
-   "metadata": {},
+   "id": "191fcbc6",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "The way we proceed in an iterative fashion is to\n",
     "1. Initialize our estimate $f_0(x)$.\n",
@@ -1379,8 +1430,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "afa5ac0d",
-   "metadata": {},
+   "id": "8257c200",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Gradient Boosting, Examples of Regression"
    ]
@@ -1388,8 +1441,11 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "bd265d3f",
-   "metadata": {},
+   "id": "97cc442d",
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt\n",
@@ -1437,60 +1493,23 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a49adb95",
-   "metadata": {},
+   "id": "e29cb10a",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Gradient Boosting, Classification Example"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
-   "id": "21ee0fda",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "(426, 30)\n",
-      "(143, 30)\n",
-      "[0.93333333 0.86666667 0.86666667 1.         1.         0.92857143\n",
-      " 1.         0.92857143 0.92857143 0.85714286]\n",
-      "Test set accuracy with Gradient boosting and scaled data: 0.98\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": 7,
+   "id": "5e71ebb0",
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
+   "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
@@ -1536,8 +1555,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "47e5b339",
-   "metadata": {},
+   "id": "7704ba08",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## XGBoost: Extreme Gradient Boosting\n",
     "\n",
@@ -1557,8 +1578,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "36ef9e63",
-   "metadata": {},
+   "id": "8f314f34",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Regression Case"
    ]
@@ -1566,8 +1589,11 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "bd3617cd",
-   "metadata": {},
+   "id": "c6b184a5",
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
    "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt\n",
@@ -1615,8 +1641,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8bb8c634",
-   "metadata": {},
+   "id": "59a68c8d",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Xgboost on the Cancer Data\n",
     "\n",
@@ -1625,81 +1653,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "id": "241155b2",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/mhjensen/miniforge3/envs/myenv/lib/python3.9/site-packages/xgboost/compat.py:36: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
-      "  from pandas import MultiIndex, Int64Index\n",
-      "/Users/mhjensen/miniforge3/envs/myenv/lib/python3.9/site-packages/xgboost/sklearn.py:1224: UserWarning: The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n",
-      "  warnings.warn(label_encoder_deprecation_msg, UserWarning)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "(426, 30)\n",
-      "(143, 30)\n",
-      "[13:41:59] WARNING: /var/folders/nz/j6p8yfhx1mv_0grj5xl4650h0000gp/T/abs_eek2t0c4ro/croots/recipe/xgboost-split_1659548960591/work/src/learner.cc:1115: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'binary:logistic' was changed from 'error' to 'logloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n",
-      "Test set accuracy with Gradient Boosting and scaled data: 1.00\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 5000x1000 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": 9,
+   "id": "6a3f228b",
+   "metadata": {
+    "collapsed": false,
+    "editable": true
+   },
+   "outputs": [],
    "source": [
     "\n",
     "import matplotlib.pyplot as plt\n",
@@ -1757,16 +1717,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4e898022",
-   "metadata": {},
+   "id": "4756e98c",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Summary of course"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "5988388a",
-   "metadata": {},
+   "id": "0d2f09bc",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## What? Me worry? No final exam in this course!\n",
     "<!-- dom:FIGURE: [figures/exam1.jpeg, width=500 frac=0.6] -->\n",
@@ -1778,8 +1742,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "73f30b11",
-   "metadata": {},
+   "id": "bedc75f8",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## What is the link between Artificial Intelligence and Machine Learning and some general Remarks\n",
     "\n",
@@ -1792,8 +1758,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "dec6ab2a",
-   "metadata": {},
+   "id": "25385cd0",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Going back to the beginning of the semester\n",
     "\n",
@@ -1815,8 +1783,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "61713d2a",
-   "metadata": {},
+   "id": "97a4cbd9",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Not so sharp distinctions\n",
     "\n",
@@ -1842,8 +1812,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2c7dfd5c",
-   "metadata": {},
+   "id": "77dada73",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Topics we have covered this year\n",
     "\n",
@@ -1856,8 +1828,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a1f41bf5",
-   "metadata": {},
+   "id": "4f784898",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Statistical analysis and optimization of data\n",
     "\n",
@@ -1879,8 +1853,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a7136cbf",
-   "metadata": {},
+   "id": "35722378",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Machine learning\n",
     "\n",
@@ -1924,8 +1900,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6e34ca63",
-   "metadata": {},
+   "id": "c5de1725",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Learning outcomes and overarching aims of this course\n",
     "\n",
@@ -1958,8 +1936,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "104edb9d",
-   "metadata": {},
+   "id": "77f0effd",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Perspective on Machine Learning\n",
     "\n",
@@ -1979,8 +1959,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "79d2ff47",
-   "metadata": {},
+   "id": "1da4f54b",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Machine Learning Research\n",
     "\n",
@@ -2000,8 +1982,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "410463c2",
-   "metadata": {},
+   "id": "960798e1",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Starting your Machine Learning Project\n",
     "\n",
@@ -2018,8 +2002,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "861a0f89",
-   "metadata": {},
+   "id": "3bb0c58d",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Choose a Model and Algorithm\n",
     "\n",
@@ -2032,8 +2018,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8723e9ee",
-   "metadata": {},
+   "id": "06e070b4",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Preparing Your Data\n",
     "\n",
@@ -2062,8 +2050,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8eb5255b",
-   "metadata": {},
+   "id": "8fc31057",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Which Activation and Weights to Choose in Neural Networks\n",
     "\n",
@@ -2082,8 +2072,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6cedd3c8",
-   "metadata": {},
+   "id": "be1f2461",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Optimization Methods and Hyperparameters\n",
     "1. Stochastic gradient descent\n",
@@ -2105,8 +2097,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fa3cdb3c",
-   "metadata": {},
+   "id": "2bf97adf",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Resampling\n",
     "\n",
@@ -2121,8 +2115,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "474deaee",
-   "metadata": {},
+   "id": "af4d612c",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Other courses on Data science and Machine Learning  at UiO\n",
     "\n",
@@ -2147,8 +2143,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c1fe720c",
-   "metadata": {},
+   "id": "02ca1e2c",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Additional courses of interest\n",
     "\n",
@@ -2159,8 +2157,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "81ff4963",
-   "metadata": {},
+   "id": "1bd70651",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## What's the future like?\n",
     "\n",
@@ -2185,8 +2185,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6815cca1",
-   "metadata": {},
+   "id": "ec41c770",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Types of Machine Learning, a repetition\n",
     "\n",
@@ -2212,8 +2214,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "83942b75",
-   "metadata": {},
+   "id": "eb4b2fd3",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Why Boltzmann machines?\n",
     "\n",
@@ -2227,8 +2231,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "28aae5b7",
-   "metadata": {},
+   "id": "666fb9a8",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Boltzmann Machines\n",
     "\n",
@@ -2247,8 +2253,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "72e08b43",
-   "metadata": {},
+   "id": "59961309",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Some similarities and differences from DNNs\n",
     "\n",
@@ -2263,8 +2271,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e9bc5428",
-   "metadata": {},
+   "id": "95115be7",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Boltzmann machines (BM)\n",
     "\n",
@@ -2284,8 +2294,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1e002295",
-   "metadata": {},
+   "id": "67240cfb",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## A standard BM setup\n",
     "\n",
@@ -2301,8 +2313,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4488ef6f",
-   "metadata": {},
+   "id": "34238f91",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## The structure of the RBM network\n",
     "\n",
@@ -2315,8 +2329,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b034bad4",
-   "metadata": {},
+   "id": "b5a2f4e8",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## The network\n",
     "\n",
@@ -2328,8 +2344,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "59c3525f",
-   "metadata": {},
+   "id": "8814bf46",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Goals\n",
     "\n",
@@ -2350,8 +2368,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bebccfe7",
-   "metadata": {},
+   "id": "7fc70e53",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Joint distribution\n",
     "\n",
@@ -2360,8 +2380,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9f9b56d5",
-   "metadata": {},
+   "id": "db48a9df",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "<!-- Equation labels as ordinary links -->\n",
     "<div id=\"_auto1\"></div>\n",
@@ -2376,16 +2398,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6508ccbb",
-   "metadata": {},
+   "id": "62a31f83",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "where $Z$ is the normalization constant or partition function, defined as"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "686e8551",
-   "metadata": {},
+   "id": "cb335a56",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "<!-- Equation labels as ordinary links -->\n",
     "<div id=\"_auto2\"></div>\n",
@@ -2400,16 +2426,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "80ad6463",
-   "metadata": {},
+   "id": "599fa487",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "It is common to ignore $T_0$ by setting it to one."
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "e7c6595e",
-   "metadata": {},
+   "id": "114dd535",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Network Elements, the energy function\n",
     "\n",
@@ -2425,8 +2455,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "24eeaa38",
-   "metadata": {},
+   "id": "211cb42a",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "$$\n",
     "E(\\hat{x},\\hat{h}) = -\\sum_{ia}^{NA}b_i^a \\alpha_i^a(x_i)-\\sum_{jd}^{MD}c_j^d \\beta_j^d(h_j)-\\sum_{ijad}^{NAMD}b_i^a \\alpha_i^a(x_i)c_j^d \\beta_j^d(h_j)w_{ij}^{ad}.\n",
@@ -2435,8 +2467,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e29eb8af",
-   "metadata": {},
+   "id": "e70c1aa0",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "Here $\\beta_j^d(h_j)$ and $\\alpha_i^a(x_j)$ are so-called transfer functions that map a given input value to a desired feature value. The labels $a$ and $d$ denote that there can be multiple transfer functions per variable. The first sum depends only on the visible units. The second on the hidden ones. **Note** that there is no connection between nodes in a layer.\n",
     "\n",
@@ -2447,8 +2481,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f0159edd",
-   "metadata": {},
+   "id": "8176921d",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Defining different types of RBMs\n",
     "There are different variants of RBMs, and the differences lie in the types of visible and hidden units we choose as well as in the implementation of the energy function $E(\\mathbf{x},\\mathbf{h})$. \n",
@@ -2460,8 +2496,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a35dca77",
-   "metadata": {},
+   "id": "d4559704",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "<!-- Equation labels as ordinary links -->\n",
     "<div id=\"_auto3\"></div>\n",
@@ -2476,8 +2514,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b6b0cc70",
-   "metadata": {},
+   "id": "6087f3b1",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "where the binary values taken on by the nodes are most commonly 0 and 1.\n",
     "\n",
@@ -2488,8 +2528,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ec274a69",
-   "metadata": {},
+   "id": "090cbae9",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "<!-- Equation labels as ordinary links -->\n",
     "<div id=\"_auto4\"></div>\n",
@@ -2504,8 +2546,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "81011851",
-   "metadata": {},
+   "id": "19c78c3f",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## More about RBMs\n",
     "1. Useful when we model continuous data (i.e., we wish $\\mathbf{x}$ to be continuous)\n",
@@ -2526,8 +2570,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "44686f56",
-   "metadata": {},
+   "id": "2c32807b",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Autoencoders: Overarching view\n",
     "\n",
@@ -2562,8 +2608,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2e493e53",
-   "metadata": {},
+   "id": "f988bcd6",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Bayesian Machine Learning\n",
     "\n",
@@ -2583,8 +2631,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0bc48b90",
-   "metadata": {},
+   "id": "c75013bd",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Reinforcement Learning\n",
     "\n",
@@ -2617,8 +2667,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d16547e3",
-   "metadata": {},
+   "id": "f0ba11de",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Transfer learning\n",
     "\n",
@@ -2636,8 +2688,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2de4ecb9",
-   "metadata": {},
+   "id": "7c3f7c5b",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Adversarial learning\n",
     "\n",
@@ -2656,8 +2710,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f55cdb1f",
-   "metadata": {},
+   "id": "964dd5f1",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Dual learning\n",
     "\n",
@@ -2674,8 +2730,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "027e5a53",
-   "metadata": {},
+   "id": "53d27ff9",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Distributed machine learning\n",
     "\n",
@@ -2687,8 +2745,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6eafe153",
-   "metadata": {},
+   "id": "263d674f",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Meta learning\n",
     "\n",
@@ -2703,8 +2763,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0c120668",
-   "metadata": {},
+   "id": "df2807f3",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## The Challenges Facing Machine Learning\n",
     "\n",
@@ -2731,8 +2793,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ce1d1942",
-   "metadata": {},
+   "id": "97618d26",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Explainable machine learning\n",
     "\n",
@@ -2758,8 +2822,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "92e30af9",
-   "metadata": {},
+   "id": "e661ff12",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Scientific Machine Learning\n",
     "\n",
@@ -2779,8 +2845,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a76f5dfb",
-   "metadata": {},
+   "id": "45e0405a",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Quantum machine learning\n",
     "\n",
@@ -2808,8 +2876,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "225aac31",
-   "metadata": {},
+   "id": "04188bac",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Quantum machine learning algorithms based on linear algebra\n",
     "\n",
@@ -2829,8 +2899,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b6842272",
-   "metadata": {},
+   "id": "6ab01276",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Quantum reinforcement learning\n",
     "\n",
@@ -2845,8 +2917,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "85f09cc0",
-   "metadata": {},
+   "id": "132951d0",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Quantum deep learning\n",
     "\n",
@@ -2866,8 +2940,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "befe6397",
-   "metadata": {},
+   "id": "06d34a06",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Social machine learning\n",
     "\n",
@@ -2885,8 +2961,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6625cb3c",
-   "metadata": {},
+   "id": "8e7e63e1",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## The last words?\n",
     "\n",
@@ -2899,8 +2977,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f247452c",
-   "metadata": {},
+   "id": "8d87fad6",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## AI/ML and some statements you may have heard (and what do they mean?)\n",
     "\n",
@@ -2917,8 +2997,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bc953bac",
-   "metadata": {},
+   "id": "52dd089f",
+   "metadata": {
+    "editable": true
+   },
    "source": [
     "## Best wishes to you all and thanks so much for your heroic efforts this semester\n",
     "\n",
@@ -2930,25 +3012,7 @@
    ]
   }
  ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.10"
-  }
- },
+ "metadata": {},
  "nbformat": 4,
  "nbformat_minor": 5
 }
diff --git a/doc/src/week47/week47.do.txt b/doc/src/week47/week47.do.txt
index 4d0ce5c9e..517eb7bf0 100644
--- a/doc/src/week47/week47.do.txt
+++ b/doc/src/week47/week47.do.txt
@@ -15,6 +15,8 @@ DATE: November 20-24, 2023
   * Thursday: Basics of decision trees, classification and regression algorithms and ensemble models 
   * Readings and Videos:
     * These lecture notes
+    * "Video of Lecture":"https://youtu.be/SpWXsvn5I9E"
+    * "Whiteboard notes":"https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2023/NotesNov23.pdf"
     * "Video on Decision trees":"https://www.youtube.com/watch?v=RmajweUFKvM&ab_channel=Simplilearn"
     * "Video on boosting methods by Hastie":"https://www.youtube.com/watch?v=wPqtzj5VZus&ab_channel=H2O.ai"
     * "Video on AdaBoost":"https://www.youtube.com/watch?v=LsK-xG1cLYA"