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 <p>Methods to perform a variety of supervised learning tasks. </p>
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 Modules</h2></td></tr>
 <tr class="memitem:group__grp__crf"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="group__grp__crf.html">Conditional Random Field</a></td></tr>
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 <tr class="memitem:group__grp__knn"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="group__grp__knn.html">k-Nearest Neighbors</a></td></tr>
 <tr class="memdesc:group__grp__knn"><td class="mdescLeft">&#160;</td><td class="mdescRight">Finds \(k\) nearest data points to the given data point and outputs majority vote value of output classes for classification, or average value of target values for regression. <br /></td></tr>
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 <tr class="memitem:group__grp__nn"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="group__grp__nn.html">Neural Network</a></td></tr>
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 <tr class="memdesc:group__grp__regml"><td class="mdescLeft">&#160;</td><td class="mdescRight">A collection of methods for modeling conditional expectation of a response variable. <br /></td></tr>
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 <tr class="memitem:group__grp__svm"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="group__grp__svm.html">Support Vector Machines</a></td></tr>
 <tr class="memdesc:group__grp__svm"><td class="mdescLeft">&#160;</td><td class="mdescRight">Solves classification and regression problems by separating data with a hyperplane or other nonlinear decision boundary. <br /></td></tr>
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 <tr class="memitem:group__grp__tree"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="group__grp__tree.html">Tree Methods</a></td></tr>
 <tr class="memdesc:group__grp__tree"><td class="mdescLeft">&#160;</td><td class="mdescRight">A collection of recursive partitioning (tree) methods. <br /></td></tr>
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	<p>Methods to perform a variety of supervised learning tasks. </p>
	<table class="memberdecls">
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	<tr class="memitem:group__grp__crf"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="group__grp__crf.html">Conditional Random Field</a></td></tr>
	<tr class="memdesc:group__grp__crf"><td class="mdescLeft"> </td><td class="mdescRight">Constructs a Conditional Random Fields (CRF) model for labeling sequential data. <br /></td></tr>
	<tr class="separator:"><td class="memSeparator" colspan="2"> </td></tr>
	<tr class="memitem:group__grp__knn"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="group__grp__knn.html">k-Nearest Neighbors</a></td></tr>
	<tr class="memdesc:group__grp__knn"><td class="mdescLeft"> </td><td class="mdescRight">Finds \(k\) nearest data points to the given data point and outputs majority vote value of output classes for classification, or average value of target values for regression. <br /></td></tr>
	<tr class="separator:"><td class="memSeparator" colspan="2"> </td></tr>
	<tr class="memitem:group__grp__nn"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="group__grp__nn.html">Neural Network</a></td></tr>
	<tr class="memdesc:group__grp__nn"><td class="mdescLeft"> </td><td class="mdescRight">Solves classification and regression problems with several fully connected layers and non-linear activation functions. <br /></td></tr>
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	<tr class="memitem:group__grp__regml"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="group__grp__regml.html">Regression Models</a></td></tr>
	<tr class="memdesc:group__grp__regml"><td class="mdescLeft"> </td><td class="mdescRight">A collection of methods for modeling conditional expectation of a response variable. <br /></td></tr>
	<tr class="separator:"><td class="memSeparator" colspan="2"> </td></tr>
	<tr class="memitem:group__grp__svm"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="group__grp__svm.html">Support Vector Machines</a></td></tr>
	<tr class="memdesc:group__grp__svm"><td class="mdescLeft"> </td><td class="mdescRight">Solves classification and regression problems by separating data with a hyperplane or other nonlinear decision boundary. <br /></td></tr>
	<tr class="separator:"><td class="memSeparator" colspan="2"> </td></tr>
	<tr class="memitem:group__grp__tree"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="group__grp__tree.html">Tree Methods</a></td></tr>
	<tr class="memdesc:group__grp__tree"><td class="mdescLeft"> </td><td class="mdescRight">A collection of recursive partitioning (tree) methods. <br /></td></tr>
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