adding typos

doc/pub/How2ReadData/html/How2ReadData-bs.html

@@ -166,7 +166,7 @@ MathJax.Hub.Config({
 <center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
 <br>
 <p>
-<center><h4>Dec 24, 2019</h4></center> <!-- date -->
+<center><h4>Dec 25, 2019</h4></center> <!-- date -->
 <br>
 <p>
 </div> <!-- end jumbotron -->
@@ -1202,8 +1202,15 @@ years etc.
 
 <p>
 Finally, another cost function is the Huber cost function used in robust regression.
-It is less sensitive to outliers in data than the squared error cost function.
-A variant for classification is also sometimes used, a quantity we will meet later. 
+
+<p>
+The rationale behind this possible cost function is its reduced
+sensitivity to outliers in the data set. In our discussions on
+dimensionality reduction and normalization of data we will meet other
+ways of dealing with outliers.
+
+<p>
+The Huber cost function is defined as
 $$
 H_{\delta}(a)={\begin{cases}{\frac {1}{2}}{a^{2}}&{\text{for }}|a|\leq \delta ,\\\delta (|a|-{\frac {1}{2}}\delta ),&{\text{otherwise.}}\end{cases}}}.
 $$

doc/pub/How2ReadData/html/How2ReadData-reveal.html

@@ -148,7 +148,7 @@ MathJax.Hub.Config({
 <center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
 <br>
 <p>&nbsp;<br>
-<center><h4>Dec 24, 2019</h4></center> <!-- date -->
+<center><h4>Dec 25, 2019</h4></center> <!-- date -->
 <br>
 
 <h2 id="___sec0">Introduction </h2>
@@ -1227,8 +1227,15 @@ years etc.
 
 <p>
 Finally, another cost function is the Huber cost function used in robust regression.
-It is less sensitive to outliers in data than the squared error cost function.
-A variant for classification is also sometimes used, a quantity we will meet later. 
+
+<p>
+The rationale behind this possible cost function is its reduced
+sensitivity to outliers in the data set. In our discussions on
+dimensionality reduction and normalization of data we will meet other
+ways of dealing with outliers.
+
+<p>
+The Huber cost function is defined as
 <p>&nbsp;<br>
 $$
 H_{\delta}(a)={\begin{cases}{\frac {1}{2}}{a^{2}}&{\text{for }}|a|\leq \delta ,\\\delta (|a|-{\frac {1}{2}}\delta ),&{\text{otherwise.}}\end{cases}}}.

doc/pub/How2ReadData/html/How2ReadData-solarized.html

@@ -135,7 +135,7 @@ MathJax.Hub.Config({
 <center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
 <br>
 <p>
-<center><h4>Dec 24, 2019</h4></center> <!-- date -->
+<center><h4>Dec 25, 2019</h4></center> <!-- date -->
 <br>
 
 <h2 id="___sec0">Introduction </h2>
@@ -1162,8 +1162,15 @@ years etc.
 
 <p>
 Finally, another cost function is the Huber cost function used in robust regression.
-It is less sensitive to outliers in data than the squared error cost function.
-A variant for classification is also sometimes used, a quantity we will meet later. 
+
+<p>
+The rationale behind this possible cost function is its reduced
+sensitivity to outliers in the data set. In our discussions on
+dimensionality reduction and normalization of data we will meet other
+ways of dealing with outliers.
+
+<p>
+The Huber cost function is defined as
 $$
 H_{\delta}(a)={\begin{cases}{\frac {1}{2}}{a^{2}}&{\text{for }}|a|\leq \delta ,\\\delta (|a|-{\frac {1}{2}}\delta ),&{\text{otherwise.}}\end{cases}}}.
 $$

doc/pub/How2ReadData/html/How2ReadData.html

@@ -140,7 +140,7 @@ MathJax.Hub.Config({
 <center>[2] <b>Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory, Michigan State University</b></center>
 <br>
 <p>
-<center><h4>Dec 24, 2019</h4></center> <!-- date -->
+<center><h4>Dec 25, 2019</h4></center> <!-- date -->
 <br>
 
 <h2 id="___sec0">Introduction </h2>
@@ -1167,8 +1167,15 @@ years etc.
 
 <p>
 Finally, another cost function is the Huber cost function used in robust regression.
-It is less sensitive to outliers in data than the squared error cost function.
-A variant for classification is also sometimes used, a quantity we will meet later. 
+
+<p>
+The rationale behind this possible cost function is its reduced
+sensitivity to outliers in the data set. In our discussions on
+dimensionality reduction and normalization of data we will meet other
+ways of dealing with outliers.
+
+<p>
+The Huber cost function is defined as
 $$
 H_{\delta}(a)={\begin{cases}{\frac {1}{2}}{a^{2}}&{\text{for }}|a|\leq \delta ,\\\delta (|a|-{\frac {1}{2}}\delta ),&{\text{otherwise.}}\end{cases}}}.
 $$

doc/pub/How2ReadData/ipynb/How2ReadData.ipynb

@@ -10,7 +10,7 @@
     "<!-- Author: -->  \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: **Dec 24, 2019**\n",
+    "Date: **Dec 25, 2019**\n",
     "\n",
     "Copyright 1999-2019, Morten Hjorth-Jensen. Released under CC Attribution-NonCommercial 4.0 license\n",
     "\n",
@@ -1458,8 +1458,13 @@
     "\n",
     "\n",
     "Finally, another cost function is the Huber cost function used in robust regression.\n",
-    "It is less sensitive to outliers in data than the squared error cost function.\n",
-    "A variant for classification is also sometimes used, a quantity we will meet later."
+    "\n",
+    "The rationale behind this possible cost function is its reduced\n",
+    "sensitivity to outliers in the data set. In our discussions on\n",
+    "dimensionality reduction and normalization of data we will meet other\n",
+    "ways of dealing with outliers.\n",
+    "\n",
+    "The Huber cost function is defined as"
    ]
   },
   {

doc/src/How2ReadData/How2ReadData.do.txt

@@ -938,8 +938,13 @@ years etc.
 
 
 Finally, another cost function is the Huber cost function used in robust regression.
-It is less sensitive to outliers in data than the squared error cost function.
-A variant for classification is also sometimes used, a quantity we will meet later. 
+
+The rationale behind this possible cost function is its reduced
+sensitivity to outliers in the data set. In our discussions on
+dimensionality reduction and normalization of data we will meet other
+ways of dealing with outliers.
+
+The Huber cost function is defined as
 !bt
 \[
 H_{\delta}(a)={\begin{cases}{\frac {1}{2}}{a^{2}}&{\text{for }}|a|\leq \delta ,\\\delta (|a|-{\frac {1}{2}}\delta ),&{\text{otherwise.}}\end{cases}}}.