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adding some other datasets to project 2

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mhjensen
2019-10-17 05:05:00 +02:00
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@@ -112,7 +112,7 @@ MathJax.Hub.Config({
<center><b>Department of Physics, University of Oslo, Norway</b></center>
<br>
<p>
<center><h4>Oct 9, 2019</h4></center> <!-- date -->
<center><h4>Oct 17, 2019</h4></center> <!-- date -->
<br>
<h2 id="___sec0">Classification and Regression, from linear and logistic regression to neural networks </h2>
@@ -152,6 +152,9 @@ has been studied in the scientific literature. This makes it easier
for you to compare and analyze your results. It is also an essential
elements of the scientific discussion.
<p>
In particular, when developing your own Logistic Regression code for classification problems, the so-called Wisconsin Cancer data (which is a binary problem, benign or malignant tumors) may be studied. You find more information about this at the <a href="https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_breast_cancer.html" target="_blank">Scikit-Learn site</a> or at the <a href="https://archive.ics.uci.edu/ml/datasets/breast+cancer+wisconsin+(original)" target="_blank">University of California at Irvine</a>. The <a href="https://compphysics.github.io/MachineLearning/doc/pub/DimRed/html/DimRed.html" target="_blank">lecture slides on dimensionality reduction have several code examples on this data set</a>.
<h3 id="___sec1">Part a): Write your Logistic Regression code, first step </h3>
<p>
@@ -206,6 +209,15 @@ Regression code.
You can compare your own results with those obtained using
<b>scikit-learn</b>.
<p>
As stated in the introduction, it can also be useful to study other datasets. In particular, when developing your own Logistic Regression code for classification problems, the so-called \
Wisconsin Cancer data (which is a binary problem, benign or malignant tumors) may be studied. You find more \
information about this at the <a href="https://scikit-learn.org/stable/modules/generated/sklearn\
.datasets.load_breast_cancer.html" target="_blank">Scikit-Learn site</a> or at the "University of California at Irvine":"https://archive.ics.uci.e\
du/ml/datasets/breast+cancer+wisconsin+(original)". The <a href="https://compphysics.github.io/MachineLearning/doc/pub/DimRed/html/DimR\
ed.html" target="_blank">lecture slides on dimensionality reduction have sev\
eral code examples on this data set</a>.
<h3 id="___sec3">Part c): Writing your own Neural Network code </h3>
<p>