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<p><a href="https://en.wikipedia.org/wiki/ADALINE">Adaptive Linear Neuron (ADALINE)</a> implementation
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<a href="#details">More...</a></p>
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<div class="textblock"><code>#include <assert.h></code><br />
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<code>#include <limits.h></code><br />
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<code>#include <math.h></code><br />
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<code>#include <stdbool.h></code><br />
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Include dependency graph for adaline_learning.c:</div>
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="nested-classes"></a>
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Data Structures</h2></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct  </td><td class="memItemRight" valign="bottom"><a class="el" href="../../d2/daa/structadaline.html">adaline</a></td></tr>
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<tr class="memdesc:"><td class="mdescLeft"> </td><td class="mdescRight">structure to hold adaline model parameters <a href="../../d2/daa/structadaline.html#details">More...</a><br /></td></tr>
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<tr class="separator:"><td class="memSeparator" colspan="2"> </td></tr>
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</table><table class="memberdecls">
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="define-members"></a>
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Macros</h2></td></tr>
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<tr class="memitem:ga555ba960994e9bccb2029764588f694f"><td class="memItemLeft" align="right" valign="top">
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#define </td><td class="memItemRight" valign="bottom"><a class="el" href="../../da/d2a/group__adaline.html#ga555ba960994e9bccb2029764588f694f">MAX_ADALINE_ITER</a>   500</td></tr>
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<tr class="memdesc:ga555ba960994e9bccb2029764588f694f"><td class="mdescLeft"> </td><td class="mdescRight">Maximum number of iterations to learn. <br /></td></tr>
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<tr class="separator:ga555ba960994e9bccb2029764588f694f"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:gab4d49d73dec94c092b7ffadba55fb020"><td class="memItemLeft" align="right" valign="top">
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#define </td><td class="memItemRight" valign="bottom"><a class="el" href="../../da/d2a/group__adaline.html#gab4d49d73dec94c092b7ffadba55fb020">ADALINE_ACCURACY</a>   1e-5</td></tr>
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<tr class="memdesc:gab4d49d73dec94c092b7ffadba55fb020"><td class="mdescLeft"> </td><td class="mdescRight">convergence accuracy \(=1\times10^{-5}\) <br /></td></tr>
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<tr class="separator:gab4d49d73dec94c092b7ffadba55fb020"><td class="memSeparator" colspan="2"> </td></tr>
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</table><table class="memberdecls">
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a>
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Functions</h2></td></tr>
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<tr class="memitem:gacd88962c5f6341e43cbc69b4a7d3485b"><td class="memItemLeft" align="right" valign="top">struct <a class="el" href="../../d2/daa/structadaline.html">adaline</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="../../da/d2a/group__adaline.html#gacd88962c5f6341e43cbc69b4a7d3485b">new_adaline</a> (const int num_features, const double eta)</td></tr>
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<tr class="memdesc:gacd88962c5f6341e43cbc69b4a7d3485b"><td class="mdescLeft"> </td><td class="mdescRight">Default constructor. <a href="../../da/d2a/group__adaline.html#gacd88962c5f6341e43cbc69b4a7d3485b">More...</a><br /></td></tr>
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<tr class="separator:gacd88962c5f6341e43cbc69b4a7d3485b"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:ga6f35caa3084772cc126ac7b20f67f665"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../da/d2a/group__adaline.html#ga6f35caa3084772cc126ac7b20f67f665">delete_adaline</a> (struct <a class="el" href="../../d2/daa/structadaline.html">adaline</a> *ada)</td></tr>
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<tr class="memdesc:ga6f35caa3084772cc126ac7b20f67f665"><td class="mdescLeft"> </td><td class="mdescRight">delete dynamically allocated memory <a href="../../da/d2a/group__adaline.html#ga6f35caa3084772cc126ac7b20f67f665">More...</a><br /></td></tr>
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<tr class="separator:ga6f35caa3084772cc126ac7b20f67f665"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:ga43576566b020c4157d4fb28f0dd45cfa"><td class="memItemLeft" align="right" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="../../da/d2a/group__adaline.html#ga43576566b020c4157d4fb28f0dd45cfa">adaline_activation</a> (double x)</td></tr>
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<tr class="memdesc:ga43576566b020c4157d4fb28f0dd45cfa"><td class="mdescLeft"> </td><td class="mdescRight"><a href="https://en.wikipedia.org/wiki/Heaviside_step_function">Heaviside activation function</a> <img src="https://upload.wikimedia.org/wikipedia/commons/d/d9/Dirac_distribution_CDF.svg" alt="" style="pointer-events: none;" width="200px" class="inline"/> <a href="../../da/d2a/group__adaline.html#ga43576566b020c4157d4fb28f0dd45cfa">More...</a><br /></td></tr>
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<tr class="separator:ga43576566b020c4157d4fb28f0dd45cfa"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:ga251695a79baa885cafdcf6d8ed4ac120"><td class="memItemLeft" align="right" valign="top">char * </td><td class="memItemRight" valign="bottom"><a class="el" href="../../da/d2a/group__adaline.html#ga251695a79baa885cafdcf6d8ed4ac120">adaline_get_weights_str</a> (const struct <a class="el" href="../../d2/daa/structadaline.html">adaline</a> *ada)</td></tr>
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<tr class="memdesc:ga251695a79baa885cafdcf6d8ed4ac120"><td class="mdescLeft"> </td><td class="mdescRight">Operator to print the weights of the model. <a href="../../da/d2a/group__adaline.html#ga251695a79baa885cafdcf6d8ed4ac120">More...</a><br /></td></tr>
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<tr class="separator:ga251695a79baa885cafdcf6d8ed4ac120"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:gac70b578aee679005fd336073969c3d94"><td class="memItemLeft" align="right" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="../../da/d2a/group__adaline.html#gac70b578aee679005fd336073969c3d94">adaline_predict</a> (struct <a class="el" href="../../d2/daa/structadaline.html">adaline</a> *ada, const double *x, double *out)</td></tr>
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<tr class="memdesc:gac70b578aee679005fd336073969c3d94"><td class="mdescLeft"> </td><td class="mdescRight">predict the output of the model for given set of features <a href="../../da/d2a/group__adaline.html#gac70b578aee679005fd336073969c3d94">More...</a><br /></td></tr>
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<tr class="separator:gac70b578aee679005fd336073969c3d94"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:ga20d3642e0a87f36fdb7bf91b023cd166"><td class="memItemLeft" align="right" valign="top">double </td><td class="memItemRight" valign="bottom"><a class="el" href="../../da/d2a/group__adaline.html#ga20d3642e0a87f36fdb7bf91b023cd166">adaline_fit_sample</a> (struct <a class="el" href="../../d2/daa/structadaline.html">adaline</a> *ada, const double *x, const int y)</td></tr>
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<tr class="memdesc:ga20d3642e0a87f36fdb7bf91b023cd166"><td class="mdescLeft"> </td><td class="mdescRight">Update the weights of the model using supervised learning for one feature vector. <a href="../../da/d2a/group__adaline.html#ga20d3642e0a87f36fdb7bf91b023cd166">More...</a><br /></td></tr>
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<tr class="separator:ga20d3642e0a87f36fdb7bf91b023cd166"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:gaa52120912e32d2893fe1c6d78da5befd"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../da/d2a/group__adaline.html#gaa52120912e32d2893fe1c6d78da5befd">adaline_fit</a> (struct <a class="el" href="../../d2/daa/structadaline.html">adaline</a> *ada, double **X, const int *y, const int N)</td></tr>
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<tr class="memdesc:gaa52120912e32d2893fe1c6d78da5befd"><td class="mdescLeft"> </td><td class="mdescRight">Update the weights of the model using supervised learning for an array of vectors. <a href="../../da/d2a/group__adaline.html#gaa52120912e32d2893fe1c6d78da5befd">More...</a><br /></td></tr>
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<tr class="separator:gaa52120912e32d2893fe1c6d78da5befd"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:ab4ecb3accf5d9e0263087e7265bbe3a9"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dd/d8c/adaline__learning_8c.html#ab4ecb3accf5d9e0263087e7265bbe3a9">test1</a> (double eta)</td></tr>
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<tr class="memdesc:ab4ecb3accf5d9e0263087e7265bbe3a9"><td class="mdescLeft"> </td><td class="mdescRight">test function to predict points in a 2D coordinate system above the line \(x=y\) as +1 and others as -1. <a href="../../dd/d8c/adaline__learning_8c.html#ab4ecb3accf5d9e0263087e7265bbe3a9">More...</a><br /></td></tr>
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<tr class="separator:ab4ecb3accf5d9e0263087e7265bbe3a9"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a05cc9a0acb524fde727a4d7b4a747ee6"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dd/d8c/adaline__learning_8c.html#a05cc9a0acb524fde727a4d7b4a747ee6">test2</a> (double eta)</td></tr>
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<tr class="memdesc:a05cc9a0acb524fde727a4d7b4a747ee6"><td class="mdescLeft"> </td><td class="mdescRight">test function to predict points in a 2D coordinate system above the line \(x+3y=-1\) as +1 and others as -1. <a href="../../dd/d8c/adaline__learning_8c.html#a05cc9a0acb524fde727a4d7b4a747ee6">More...</a><br /></td></tr>
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<tr class="separator:a05cc9a0acb524fde727a4d7b4a747ee6"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a3f37b9f073f7e57fd0b39d70718af1b1"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dd/d8c/adaline__learning_8c.html#a3f37b9f073f7e57fd0b39d70718af1b1">test3</a> (double eta)</td></tr>
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<tr class="memdesc:a3f37b9f073f7e57fd0b39d70718af1b1"><td class="mdescLeft"> </td><td class="mdescRight">test function to predict points in a 3D coordinate system lying within the sphere of radius 1 and centre at origin as +1 and others as -1. <a href="../../dd/d8c/adaline__learning_8c.html#a3f37b9f073f7e57fd0b39d70718af1b1">More...</a><br /></td></tr>
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<tr class="separator:a3f37b9f073f7e57fd0b39d70718af1b1"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a3c04138a5bfe5d72780bb7e82a18e627"><td class="memItemLeft" align="right" valign="top"><a id="a3c04138a5bfe5d72780bb7e82a18e627"></a>
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int </td><td class="memItemRight" valign="bottom"><a class="el" href="../../dd/d8c/adaline__learning_8c.html#a3c04138a5bfe5d72780bb7e82a18e627">main</a> (int argc, char **argv)</td></tr>
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<tr class="memdesc:a3c04138a5bfe5d72780bb7e82a18e627"><td class="mdescLeft"> </td><td class="mdescRight">Main function. <br /></td></tr>
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<tr class="separator:a3c04138a5bfe5d72780bb7e82a18e627"><td class="memSeparator" colspan="2"> </td></tr>
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</table>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
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<div class="textblock"><p><a href="https://en.wikipedia.org/wiki/ADALINE">Adaptive Linear Neuron (ADALINE)</a> implementation </p>
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<p><img src="https://upload.wikimedia.org/wikipedia/commons/b/be/Adaline_flow_chart.gif" alt="" width="200px" class="inline"/> <a href="https://commons.wikimedia.org/wiki/File:Adaline_flow_chart.gif">source</a> ADALINE is one of the first and simplest single layer artificial neural network. The algorithm essentially implements a linear function </p><p class="formulaDsp">
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\[ f\left(x_0,x_1,x_2,\ldots\right) = \sum_j x_jw_j+\theta \]
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</p>
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<p> where \(x_j\) are the input features of a sample, \(w_j\) are the coefficients of the linear function and \(\theta\) is a constant. If we know the \(w_j\), then for any given set of features, \(y\) can be computed. Computing the \(w_j\) is a supervised learning algorithm wherein a set of features and their corresponding outputs are given and weights are computed using stochastic gradient descent method. </p><dl class="section author"><dt>Author</dt><dd><a href="https://github.com/kvedala">Krishna Vedala</a> </dd></dl>
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</div><h2 class="groupheader">Function Documentation</h2>
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<a id="ab4ecb3accf5d9e0263087e7265bbe3a9"></a>
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<h2 class="memtitle"><span class="permalink"><a href="#ab4ecb3accf5d9e0263087e7265bbe3a9">◆ </a></span>test1()</h2>
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<div class="memitem">
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<td class="memname">void test1 </td>
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<td>(</td>
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<td class="paramtype">double </td>
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<td class="paramname"><em>eta</em></td><td>)</td>
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<p>test function to predict points in a 2D coordinate system above the line \(x=y\) as +1 and others as -1. </p>
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<p>Note that each point is defined by 2 values or 2 features. </p><dl class="params"><dt>Parameters</dt><dd>
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<table class="params">
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<tr><td class="paramdir">[in]</td><td class="paramname">eta</td><td>learning rate (optional, default=0.01) </td></tr>
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</dd>
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<div class="fragment"><div class="line"><a name="l00226"></a><span class="lineno"> 226</span> {</div>
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<div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <span class="keyword">struct </span><a class="code" href="../../d2/daa/structadaline.html">adaline</a> ada = <a class="code" href="../../da/d2a/group__adaline.html#gacd88962c5f6341e43cbc69b4a7d3485b">new_adaline</a>(2, <a class="code" href="../../d2/daa/structadaline.html#a85dbd7cce6195d11ebb388220b96bde2">eta</a>); <span class="comment">// 2 features</span></div>
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<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  </div>
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<div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> N = 10; <span class="comment">// number of sample points</span></div>
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<div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  <span class="keyword">const</span> <span class="keywordtype">double</span> saved_X[10][2] = {{0, 1}, {1, -2}, {2, 3}, {3, -1},</div>
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<div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  {4, 1}, {6, -5}, {-7, -3}, {-8, 5},</div>
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<div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  {-9, 2}, {-10, -15}};</div>
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<div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  </div>
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<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  <span class="keywordtype">double</span> **X = (<span class="keywordtype">double</span> **)malloc(N * <span class="keyword">sizeof</span>(<span class="keywordtype">double</span> *));</div>
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<div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> Y[10] = {1, -1, 1, -1, -1,</div>
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<div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  -1, 1, 1, 1, -1}; <span class="comment">// corresponding y-values</span></div>
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<div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < N; i++)</div>
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<div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  {</div>
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<div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  X[i] = (<span class="keywordtype">double</span> *)saved_X[i];</div>
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<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  }</div>
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<div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  </div>
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<div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  printf(<span class="stringliteral">"------- Test 1 -------\n"</span>);</div>
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<div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  printf(<span class="stringliteral">"Model before fit: %s"</span>, <a class="code" href="../../da/d2a/group__adaline.html#ga251695a79baa885cafdcf6d8ed4ac120">adaline_get_weights_str</a>(&ada));</div>
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<div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  </div>
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<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  <a class="code" href="../../da/d2a/group__adaline.html#gaa52120912e32d2893fe1c6d78da5befd">adaline_fit</a>(&ada, X, Y, N);</div>
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<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  printf(<span class="stringliteral">"Model after fit: %s\n"</span>, <a class="code" href="../../da/d2a/group__adaline.html#ga251695a79baa885cafdcf6d8ed4ac120">adaline_get_weights_str</a>(&ada));</div>
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<div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  </div>
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<div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  <span class="keywordtype">double</span> test_x[] = {5, -3};</div>
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<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  <span class="keywordtype">int</span> pred = <a class="code" href="../../da/d2a/group__adaline.html#gac70b578aee679005fd336073969c3d94">adaline_predict</a>(&ada, test_x, NULL);</div>
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<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  printf(<span class="stringliteral">"Predict for x=(5,-3): % d"</span>, pred);</div>
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<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  assert(pred == -1);</div>
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<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  printf(<span class="stringliteral">" ...passed\n"</span>);</div>
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<div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  </div>
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<div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="keywordtype">double</span> test_x2[] = {5, 8};</div>
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<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  pred = <a class="code" href="../../da/d2a/group__adaline.html#gac70b578aee679005fd336073969c3d94">adaline_predict</a>(&ada, test_x2, NULL);</div>
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<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  printf(<span class="stringliteral">"Predict for x=(5, 8): % d"</span>, pred);</div>
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<div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  assert(pred == 1);</div>
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<div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  printf(<span class="stringliteral">" ...passed\n"</span>);</div>
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<div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  </div>
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<div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <span class="comment">// for (int i = 0; i < N; i++)</span></div>
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<div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <span class="comment">// free(X[i]);</span></div>
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<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  free(X);</div>
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<div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  <a class="code" href="../../da/d2a/group__adaline.html#ga6f35caa3084772cc126ac7b20f67f665">delete_adaline</a>(&ada);</div>
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<div class="line"><a name="l00264"></a><span class="lineno"> 264</span> }</div>
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<div class="center"><div class="zoom"><iframe scrolling="no" frameborder="0" src="../../dd/d8c/adaline__learning_8c_ab4ecb3accf5d9e0263087e7265bbe3a9_cgraph.svg" width="100%" height="480"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a05cc9a0acb524fde727a4d7b4a747ee6">◆ </a></span>test2()</h2>
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<td class="memname">void test2 </td>
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<td>(</td>
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<td class="paramtype">double </td>
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<td class="paramname"><em>eta</em></td><td>)</td>
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<td></td>
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<p>test function to predict points in a 2D coordinate system above the line \(x+3y=-1\) as +1 and others as -1. </p>
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<p>Note that each point is defined by 2 values or 2 features. The function will create random sample points for training and test purposes. </p><dl class="params"><dt>Parameters</dt><dd>
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<table class="params">
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<tr><td class="paramdir">[in]</td><td class="paramname">eta</td><td>learning rate (optional, default=0.01) </td></tr>
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</table>
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</dd>
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</dl>
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<div class="fragment"><div class="line"><a name="l00274"></a><span class="lineno"> 274</span> {</div>
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<div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  <span class="keyword">struct </span><a class="code" href="../../d2/daa/structadaline.html">adaline</a> ada = <a class="code" href="../../da/d2a/group__adaline.html#gacd88962c5f6341e43cbc69b4a7d3485b">new_adaline</a>(2, <a class="code" href="../../d2/daa/structadaline.html#a85dbd7cce6195d11ebb388220b96bde2">eta</a>); <span class="comment">// 2 features</span></div>
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<div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  </div>
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<div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> N = 50; <span class="comment">// number of sample points</span></div>
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<div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  </div>
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<div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <span class="keywordtype">double</span> **X = (<span class="keywordtype">double</span> **)malloc(N * <span class="keyword">sizeof</span>(<span class="keywordtype">double</span> *));</div>
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<div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <span class="keywordtype">int</span> *Y = (<span class="keywordtype">int</span> *)malloc(N * <span class="keyword">sizeof</span>(<span class="keywordtype">int</span>)); <span class="comment">// corresponding y-values</span></div>
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<div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < N; i++) X[i] = (<span class="keywordtype">double</span> *)malloc(2 * <span class="keyword">sizeof</span>(<span class="keywordtype">double</span>));</div>
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<div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  </div>
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<div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  <span class="comment">// generate sample points in the interval</span></div>
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<div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  <span class="comment">// [-range2/100 , (range2-1)/100]</span></div>
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<div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="keywordtype">int</span> <a class="code" href="../../df/dea/structdata.html">range</a> = 500; <span class="comment">// sample points full-range</span></div>
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<div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  <span class="keywordtype">int</span> range2 = <a class="code" href="../../df/dea/structdata.html">range</a> >> 1; <span class="comment">// sample points half-range</span></div>
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<div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < N; i++)</div>
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<div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  {</div>
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<div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <span class="keywordtype">double</span> x0 = ((rand() % <a class="code" href="../../df/dea/structdata.html">range</a>) - range2) / 100.f;</div>
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<div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <span class="keywordtype">double</span> x1 = ((rand() % <a class="code" href="../../df/dea/structdata.html">range</a>) - range2) / 100.f;</div>
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<div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  X[i][0] = x0;</div>
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<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  X[i][1] = x1;</div>
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<div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  Y[i] = (x0 + 3. * x1) > -1 ? 1 : -1;</div>
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<div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  }</div>
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<div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  </div>
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<div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  printf(<span class="stringliteral">"------- Test 2 -------\n"</span>);</div>
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<div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  printf(<span class="stringliteral">"Model before fit: %s"</span>, <a class="code" href="../../da/d2a/group__adaline.html#ga251695a79baa885cafdcf6d8ed4ac120">adaline_get_weights_str</a>(&ada));</div>
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<div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  </div>
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<div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <a class="code" href="../../da/d2a/group__adaline.html#gaa52120912e32d2893fe1c6d78da5befd">adaline_fit</a>(&ada, X, Y, N);</div>
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<div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  printf(<span class="stringliteral">"Model after fit: %s\n"</span>, <a class="code" href="../../da/d2a/group__adaline.html#ga251695a79baa885cafdcf6d8ed4ac120">adaline_get_weights_str</a>(&ada));</div>
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<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  </div>
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<div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <span class="keywordtype">int</span> N_test_cases = 5;</div>
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<div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <span class="keywordtype">double</span> test_x[2];</div>
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<div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < N_test_cases; i++)</div>
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<div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  {</div>
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<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <span class="keywordtype">double</span> x0 = ((rand() % <a class="code" href="../../df/dea/structdata.html">range</a>) - range2) / 100.f;</div>
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<div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  <span class="keywordtype">double</span> x1 = ((rand() % <a class="code" href="../../df/dea/structdata.html">range</a>) - range2) / 100.f;</div>
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<div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  </div>
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<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  test_x[0] = x0;</div>
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<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  test_x[1] = x1;</div>
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<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <span class="keywordtype">int</span> pred = <a class="code" href="../../da/d2a/group__adaline.html#gac70b578aee679005fd336073969c3d94">adaline_predict</a>(&ada, test_x, NULL);</div>
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<div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  printf(<span class="stringliteral">"Predict for x=(% 3.2f,% 3.2f): % d"</span>, x0, x1, pred);</div>
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<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  </div>
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<div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  <span class="keywordtype">int</span> expected_val = (x0 + 3. * x1) > -1 ? 1 : -1;</div>
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<div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  assert(pred == expected_val);</div>
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<div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  printf(<span class="stringliteral">" ...passed\n"</span>);</div>
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<div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  }</div>
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<div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  </div>
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<div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < N; i++) free(X[i]);</div>
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<div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  free(X);</div>
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<div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  free(Y);</div>
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<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <a class="code" href="../../da/d2a/group__adaline.html#ga6f35caa3084772cc126ac7b20f67f665">delete_adaline</a>(&ada);</div>
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<div class="line"><a name="l00323"></a><span class="lineno"> 323</span> }</div>
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<div class="center"><div class="zoom"><iframe scrolling="no" frameborder="0" src="../../dd/d8c/adaline__learning_8c_a05cc9a0acb524fde727a4d7b4a747ee6_cgraph.svg" width="100%" height="480"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe></div>
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<h2 class="memtitle"><span class="permalink"><a href="#a3f37b9f073f7e57fd0b39d70718af1b1">◆ </a></span>test3()</h2>
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<td class="memname">void test3 </td>
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<td>(</td>
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<td class="paramtype">double </td>
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<td class="paramname"><em>eta</em></td><td>)</td>
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<p>test function to predict points in a 3D coordinate system lying within the sphere of radius 1 and centre at origin as +1 and others as -1. </p>
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<p>Note that each point is defined by 3 values but we use 6 features. The function will create random sample points for training and test purposes. The sphere centred at origin and radius 1 is defined as: \(x^2+y^2+z^2=r^2=1\) and if the \(r^2<1\), point lies within the sphere else, outside.</p>
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<dl class="params"><dt>Parameters</dt><dd>
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<table class="params">
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<tr><td class="paramdir">[in]</td><td class="paramname">eta</td><td>learning rate (optional, default=0.01) </td></tr>
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</dd>
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<div class="fragment"><div class="line"><a name="l00337"></a><span class="lineno"> 337</span> {</div>
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<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <span class="keyword">struct </span><a class="code" href="../../d2/daa/structadaline.html">adaline</a> ada = <a class="code" href="../../da/d2a/group__adaline.html#gacd88962c5f6341e43cbc69b4a7d3485b">new_adaline</a>(6, <a class="code" href="../../d2/daa/structadaline.html#a85dbd7cce6195d11ebb388220b96bde2">eta</a>); <span class="comment">// 2 features</span></div>
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<div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  </div>
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<div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> N = 50; <span class="comment">// number of sample points</span></div>
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<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  </div>
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<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <span class="keywordtype">double</span> **X = (<span class="keywordtype">double</span> **)malloc(N * <span class="keyword">sizeof</span>(<span class="keywordtype">double</span> *));</div>
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<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <span class="keywordtype">int</span> *Y = (<span class="keywordtype">int</span> *)malloc(N * <span class="keyword">sizeof</span>(<span class="keywordtype">int</span>)); <span class="comment">// corresponding y-values</span></div>
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<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < N; i++) X[i] = (<span class="keywordtype">double</span> *)malloc(6 * <span class="keyword">sizeof</span>(<span class="keywordtype">double</span>));</div>
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<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  </div>
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<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <span class="comment">// generate sample points in the interval</span></div>
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<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <span class="comment">// [-range2/100 , (range2-1)/100]</span></div>
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<div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <span class="keywordtype">int</span> <a class="code" href="../../df/dea/structdata.html">range</a> = 200; <span class="comment">// sample points full-range</span></div>
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<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  <span class="keywordtype">int</span> range2 = <a class="code" href="../../df/dea/structdata.html">range</a> >> 1; <span class="comment">// sample points half-range</span></div>
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<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < N; i++)</div>
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<div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  {</div>
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<div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <span class="keywordtype">double</span> x0 = ((rand() % <a class="code" href="../../df/dea/structdata.html">range</a>) - range2) / 100.f;</div>
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<div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <span class="keywordtype">double</span> x1 = ((rand() % <a class="code" href="../../df/dea/structdata.html">range</a>) - range2) / 100.f;</div>
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<div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <span class="keywordtype">double</span> x2 = ((rand() % <a class="code" href="../../df/dea/structdata.html">range</a>) - range2) / 100.f;</div>
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<div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  X[i][0] = x0;</div>
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<div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  X[i][1] = x1;</div>
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<div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  X[i][2] = x2;</div>
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<div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  X[i][3] = x0 * x0;</div>
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<div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  X[i][4] = x1 * x1;</div>
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<div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  X[i][5] = x2 * x2;</div>
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<div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  Y[i] = (x0 * x0 + x1 * x1 + x2 * x2) <= 1 ? 1 : -1;</div>
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<div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  }</div>
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<div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  </div>
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<div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  printf(<span class="stringliteral">"------- Test 3 -------\n"</span>);</div>
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<div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  printf(<span class="stringliteral">"Model before fit: %s"</span>, <a class="code" href="../../da/d2a/group__adaline.html#ga251695a79baa885cafdcf6d8ed4ac120">adaline_get_weights_str</a>(&ada));</div>
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<div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  </div>
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<div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  <a class="code" href="../../da/d2a/group__adaline.html#gaa52120912e32d2893fe1c6d78da5befd">adaline_fit</a>(&ada, X, Y, N);</div>
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<div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  printf(<span class="stringliteral">"Model after fit: %s\n"</span>, <a class="code" href="../../da/d2a/group__adaline.html#ga251695a79baa885cafdcf6d8ed4ac120">adaline_get_weights_str</a>(&ada));</div>
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<div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  </div>
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<div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  <span class="keywordtype">int</span> N_test_cases = 5;</div>
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<div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  <span class="keywordtype">double</span> test_x[6];</div>
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<div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < N_test_cases; i++)</div>
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<div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  {</div>
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<div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <span class="keywordtype">double</span> x0 = ((rand() % <a class="code" href="../../df/dea/structdata.html">range</a>) - range2) / 100.f;</div>
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<div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="keywordtype">double</span> x1 = ((rand() % <a class="code" href="../../df/dea/structdata.html">range</a>) - range2) / 100.f;</div>
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<div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <span class="keywordtype">double</span> x2 = ((rand() % <a class="code" href="../../df/dea/structdata.html">range</a>) - range2) / 100.f;</div>
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<div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  test_x[0] = x0;</div>
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<div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  test_x[1] = x1;</div>
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<div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  test_x[2] = x2;</div>
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<div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  test_x[3] = x0 * x0;</div>
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<div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  test_x[4] = x1 * x1;</div>
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<div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  test_x[5] = x2 * x2;</div>
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<div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <span class="keywordtype">int</span> pred = <a class="code" href="../../da/d2a/group__adaline.html#gac70b578aee679005fd336073969c3d94">adaline_predict</a>(&ada, test_x, NULL);</div>
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<div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  printf(<span class="stringliteral">"Predict for x=(% 3.2f,% 3.2f): % d"</span>, x0, x1, pred);</div>
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<div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  </div>
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<div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  <span class="keywordtype">int</span> expected_val = (x0 * x0 + x1 * x1 + x2 * x2) <= 1 ? 1 : -1;</div>
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<div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  assert(pred == expected_val);</div>
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<div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  printf(<span class="stringliteral">" ...passed\n"</span>);</div>
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<div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  }</div>
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<div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  </div>
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<div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < N; i++) free(X[i]);</div>
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<div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  free(X);</div>
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<div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  free(Y);</div>
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<div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  <a class="code" href="../../da/d2a/group__adaline.html#ga6f35caa3084772cc126ac7b20f67f665">delete_adaline</a>(&ada);</div>
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<div class="line"><a name="l00395"></a><span class="lineno"> 395</span> }</div>
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Here is the call graph for this function:</div>
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<div class="center"><div class="zoom"><iframe scrolling="no" frameborder="0" src="../../dd/d8c/adaline__learning_8c_a3f37b9f073f7e57fd0b39d70718af1b1_cgraph.svg" width="100%" height="480"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe></div>
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<div class="ttc" id="agroup__adaline_html_gaa52120912e32d2893fe1c6d78da5befd"><div class="ttname"><a href="../../da/d2a/group__adaline.html#gaa52120912e32d2893fe1c6d78da5befd">adaline_fit</a></div><div class="ttdeci">void adaline_fit(struct adaline *ada, double **X, const int *y, const int N)</div><div class="ttdoc">Update the weights of the model using supervised learning for an array of vectors.</div><div class="ttdef"><b>Definition:</b> adaline_learning.c:184</div></div>
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<div class="ttc" id="astructdata_html"><div class="ttname"><a href="../../df/dea/structdata.html">data</a></div><div class="ttdef"><b>Definition:</b> prime_factoriziation.c:25</div></div>
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<div class="ttc" id="astructadaline_html_a85dbd7cce6195d11ebb388220b96bde2"><div class="ttname"><a href="../../d2/daa/structadaline.html#a85dbd7cce6195d11ebb388220b96bde2">adaline::eta</a></div><div class="ttdeci">double eta</div><div class="ttdoc">learning rate of the algorithm</div><div class="ttdef"><b>Definition:</b> adaline_learning.c:45</div></div>
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<div class="ttc" id="agroup__adaline_html_ga6f35caa3084772cc126ac7b20f67f665"><div class="ttname"><a href="../../da/d2a/group__adaline.html#ga6f35caa3084772cc126ac7b20f67f665">delete_adaline</a></div><div class="ttdeci">void delete_adaline(struct adaline *ada)</div><div class="ttdoc">delete dynamically allocated memory</div><div class="ttdef"><b>Definition:</b> adaline_learning.c:89</div></div>
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<div class="ttc" id="agroup__adaline_html_gac70b578aee679005fd336073969c3d94"><div class="ttname"><a href="../../da/d2a/group__adaline.html#gac70b578aee679005fd336073969c3d94">adaline_predict</a></div><div class="ttdeci">int adaline_predict(struct adaline *ada, const double *x, double *out)</div><div class="ttdoc">predict the output of the model for given set of features</div><div class="ttdef"><b>Definition:</b> adaline_learning.c:136</div></div>
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<div class="ttc" id="astructadaline_html"><div class="ttname"><a href="../../d2/daa/structadaline.html">adaline</a></div><div class="ttdoc">structure to hold adaline model parameters</div><div class="ttdef"><b>Definition:</b> adaline_learning.c:44</div></div>
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<div class="ttc" id="agroup__adaline_html_ga251695a79baa885cafdcf6d8ed4ac120"><div class="ttname"><a href="../../da/d2a/group__adaline.html#ga251695a79baa885cafdcf6d8ed4ac120">adaline_get_weights_str</a></div><div class="ttdeci">char * adaline_get_weights_str(const struct adaline *ada)</div><div class="ttdoc">Operator to print the weights of the model.</div><div class="ttdef"><b>Definition:</b> adaline_learning.c:112</div></div>
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<div class="ttc" id="agroup__adaline_html_gacd88962c5f6341e43cbc69b4a7d3485b"><div class="ttname"><a href="../../da/d2a/group__adaline.html#gacd88962c5f6341e43cbc69b4a7d3485b">new_adaline</a></div><div class="ttdeci">struct adaline new_adaline(const int num_features, const double eta)</div><div class="ttdoc">Default constructor.</div><div class="ttdef"><b>Definition:</b> adaline_learning.c:59</div></div>
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