backup/C-Plus-Plus
1
0
Fork 0
mirror of https://github.com/TheAlgorithms/C-Plus-Plus.git synced 2026-03-22 04:42:10 +08:00
Code Issues Projects Releases Wiki Activity
Files
fc46f441ae1ee9dfe2ca35ecabe40ee4065a26d0
C-Plus-Plus/d8/d77/namespacemachine__learning.html
github-actions e45ed6426c Documentation for 8cd25f4f8a
2020-06-25 14:04:20 +00:00

625 lines
61 KiB
HTML
Raw Blame History

<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "https://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/>
<meta http-equiv="X-UA-Compatible" content="IE=9"/>
<meta name="generator" content="Doxygen 1.8.18"/>
<meta name="viewport" content="width=device-width, initial-scale=1"/>
<title>Algorithms_in_C++: machine_learning Namespace Reference</title>
<link href="../../tabs.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="../../jquery.js"></script>
<script type="text/javascript" src="../../dynsections.js"></script>
<link href="../../navtree.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="../../resize.js"></script>
<script type="text/javascript" src="../../navtreedata.js"></script>
<script type="text/javascript" src="../../navtree.js"></script>
<link href="../../search/search.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="../../search/searchdata.js"></script>
<script type="text/javascript" src="../../search/search.js"></script>
<script type="text/x-mathjax-config">
MathJax.Hub.Config({
extensions: ["tex2jax.js", "TeX/AMSmath.js", "TeX/AMSsymbols.js"],
jax: ["input/TeX","output/HTML-CSS"],
});
</script>
<script type="text/javascript" async="async" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.7/MathJax.js?config=TeX-MML-AM_CHTML/MathJax.js"></script>
<link href="../../doxygen.css" rel="stylesheet" type="text/css" />
</head>
<body>
<div id="top"><!-- do not remove this div, it is closed by doxygen! -->
<div id="titlearea">
<table cellspacing="0" cellpadding="0">
<tbody>
<tr style="height: 56px;">
<td id="projectalign" style="padding-left: 0.5em;">
<div id="projectname">Algorithms_in_C++
&#160;<span id="projectnumber">1.0.0</span>
</div>
<div id="projectbrief">Set of algorithms implemented in C++.</div>
</td>
</tr>
</tbody>
</table>
</div>
<!-- end header part -->
<!-- Generated by Doxygen 1.8.18 -->
<script type="text/javascript">
/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&amp;dn=gpl-2.0.txt GPL-v2 */
var searchBox = new SearchBox("searchBox", "../../search",false,'Search');
/* @license-end */
</script>
<script type="text/javascript" src="../../menudata.js"></script>
<script type="text/javascript" src="../../menu.js"></script>
<script type="text/javascript">
/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&amp;dn=gpl-2.0.txt GPL-v2 */
$(function() {
initMenu('../../',true,false,'search.php','Search');
$(document).ready(function() { init_search(); });
});
/* @license-end */</script>
<div id="main-nav"></div>
</div><!-- top -->
<div id="side-nav" class="ui-resizable side-nav-resizable">
<div id="nav-tree">
<div id="nav-tree-contents">
<div id="nav-sync" class="sync"></div>
</div>
</div>
<div id="splitbar" style="-moz-user-select:none;"
class="ui-resizable-handle">
</div>
</div>
<script type="text/javascript">
/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&amp;dn=gpl-2.0.txt GPL-v2 */
$(document).ready(function(){initNavTree('d8/d77/namespacemachine__learning.html','../../'); initResizable(); });
/* @license-end */
</script>
<div id="doc-content">
<!-- window showing the filter options -->
<div id="MSearchSelectWindow"
onmouseover="return searchBox.OnSearchSelectShow()"
onmouseout="return searchBox.OnSearchSelectHide()"
onkeydown="return searchBox.OnSearchSelectKey(event)">
</div>
<!-- iframe showing the search results (closed by default) -->
<div id="MSearchResultsWindow">
<iframe src="javascript:void(0)" frameborder="0"
name="MSearchResults" id="MSearchResults">
</iframe>
</div>
<div class="header">
<div class="summary">
<a href="#nested-classes">Classes</a> &#124;
<a href="#func-members">Functions</a> </div>
<div class="headertitle">
<div class="title">machine_learning Namespace Reference<div class="ingroups"><a class="el" href="../../d9/d66/group__machine__learning.html">Machine Learning Algorithms</a></div></div> </div>
</div><!--header-->
<div class="contents">
<p>Machine learning algorithms.
<a href="../../d8/d77/namespacemachine__learning.html#details">More...</a></p>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="nested-classes"></a>
Classes</h2></td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="../../d6/d30/classmachine__learning_1_1adaline.html">adaline</a></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a>
Functions</h2></td></tr>
<tr class="memitem:a1d577f5d95b774ae97eb6838852d0df5"><td class="memItemLeft" align="right" valign="top">int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d77/namespacemachine__learning.html#a1d577f5d95b774ae97eb6838852d0df5">save_u_matrix</a> (const char *fname, const <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt;&gt;&gt; &amp;W)</td></tr>
<tr class="separator:a1d577f5d95b774ae97eb6838852d0df5"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac4010fe3a52a74e8b5b1aaadfe38b46f"><td class="memItemLeft" align="right" valign="top">double&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d77/namespacemachine__learning.html#ac4010fe3a52a74e8b5b1aaadfe38b46f">update_weights</a> (const <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt; &amp;X, <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt;&gt;&gt; *W, <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt;&gt; *D, double alpha, int R)</td></tr>
<tr class="separator:ac4010fe3a52a74e8b5b1aaadfe38b46f"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:adc731720947b4bc2ab047c141e7d0299"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d77/namespacemachine__learning.html#adc731720947b4bc2ab047c141e7d0299">kohonen_som</a> (const <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt;&gt; &amp;X, <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt;&gt;&gt; *W, double alpha_min)</td></tr>
<tr class="separator:adc731720947b4bc2ab047c141e7d0299"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a361674452869413536ee501f053129a8"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d77/namespacemachine__learning.html#a361674452869413536ee501f053129a8">update_weights</a> (const <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt; &amp;x, <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt;&gt; *W, <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt; *D, double alpha, int R)</td></tr>
<tr class="separator:a361674452869413536ee501f053129a8"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:acc6a28f40512dbda75ab1a3969248898"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="../../d8/d77/namespacemachine__learning.html#acc6a28f40512dbda75ab1a3969248898">kohonen_som_tracer</a> (const <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt;&gt; &amp;X, <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt;&gt; *W, double alpha_min)</td></tr>
<tr class="separator:acc6a28f40512dbda75ab1a3969248898"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table>
<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>Machine learning algorithms. </p>
</div><h2 class="groupheader">Function Documentation</h2>
<a id="adc731720947b4bc2ab047c141e7d0299"></a>
<h2 class="memtitle"><span class="permalink"><a href="#adc731720947b4bc2ab047c141e7d0299">&#9670;&nbsp;</a></span>kohonen_som()</h2>
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">void machine_learning::kohonen_som </td>
<td>(</td>
<td class="paramtype">const <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt;&gt; &amp;&#160;</td>
<td class="paramname"><em>X</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt;&gt;&gt; *&#160;</td>
<td class="paramname"><em>W</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">double&#160;</td>
<td class="paramname"><em>alpha_min</em>&#160;</td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
</tr>
</table>
</div><div class="memdoc">
<p>Apply incremental algorithm with updating neighborhood and learning rates on all samples in the given datset.</p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">X</td><td>data set </td></tr>
<tr><td class="paramdir">[in,out]</td><td class="paramname">W</td><td>weights matrix </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">alpha_min</td><td>terminal value of alpha </td></tr>
</table>
</dd>
</dl>
<div class="fragment"><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>&#160; {</div>
<div class="line"><a name="l00264"></a><span class="lineno"> 264</span>&#160; <span class="keywordtype">int</span> num_samples = X.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>(); <span class="comment">// number of rows</span></div>
<div class="line"><a name="l00265"></a><span class="lineno"> 265</span>&#160; <span class="keywordtype">int</span> num_features = X[0].<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>(); <span class="comment">// number of columns</span></div>
<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>&#160; <span class="keywordtype">int</span> num_out = W-&gt;<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>(); <span class="comment">// output matrix size</span></div>
<div class="line"><a name="l00267"></a><span class="lineno"> 267</span>&#160; <span class="keywordtype">int</span> R = num_out &gt;&gt; 2, iter = 0;</div>
<div class="line"><a name="l00268"></a><span class="lineno"> 268</span>&#160; <span class="keywordtype">double</span> alpha = 1.f;</div>
<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>&#160; </div>
<div class="line"><a name="l00270"></a><span class="lineno"> 270</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector&lt;std::valarray&lt;double&gt;</a>&gt; D(num_out);</div>
<div class="line"><a name="l00271"></a><span class="lineno"> 271</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; num_out; i++) D[i] = std::valarray&lt;double&gt;(num_out);</div>
<div class="line"><a name="l00272"></a><span class="lineno"> 272</span>&#160; </div>
<div class="line"><a name="l00273"></a><span class="lineno"> 273</span>&#160; <span class="keywordtype">double</span> dmin = 1.f; <span class="comment">// average minimum distance of all samples</span></div>
<div class="line"><a name="l00274"></a><span class="lineno"> 274</span>&#160; <span class="keywordtype">double</span> past_dmin = 1.f; <span class="comment">// average minimum distance of all samples</span></div>
<div class="line"><a name="l00275"></a><span class="lineno"> 275</span>&#160; <span class="keywordtype">double</span> dmin_ratio = 1.f; <span class="comment">// change per step</span></div>
<div class="line"><a name="l00276"></a><span class="lineno"> 276</span>&#160; </div>
<div class="line"><a name="l00277"></a><span class="lineno"> 277</span>&#160; <span class="comment">// Loop alpha from 1 to slpha_min</span></div>
<div class="line"><a name="l00278"></a><span class="lineno"> 278</span>&#160; <span class="keywordflow">for</span> (; alpha &gt; 0 &amp;&amp; dmin_ratio &gt; 1e-5; alpha -= 1e-4, iter++) {</div>
<div class="line"><a name="l00279"></a><span class="lineno"> 279</span>&#160; <span class="comment">// Loop for each sample pattern in the data set</span></div>
<div class="line"><a name="l00280"></a><span class="lineno"> 280</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> sample = 0; sample &lt; num_samples; sample++) {</div>
<div class="line"><a name="l00281"></a><span class="lineno"> 281</span>&#160; <span class="comment">// update weights for the current input pattern sample</span></div>
<div class="line"><a name="l00282"></a><span class="lineno"> 282</span>&#160; dmin += <a class="code" href="../../d8/d77/namespacemachine__learning.html#ac4010fe3a52a74e8b5b1aaadfe38b46f">update_weights</a>(X[sample], W, &amp;D, alpha, R);</div>
<div class="line"><a name="l00283"></a><span class="lineno"> 283</span>&#160; }</div>
<div class="line"><a name="l00284"></a><span class="lineno"> 284</span>&#160; </div>
<div class="line"><a name="l00285"></a><span class="lineno"> 285</span>&#160; <span class="comment">// every 100th iteration, reduce the neighborhood range</span></div>
<div class="line"><a name="l00286"></a><span class="lineno"> 286</span>&#160; <span class="keywordflow">if</span> (iter % 300 == 0 &amp;&amp; R &gt; 1)</div>
<div class="line"><a name="l00287"></a><span class="lineno"> 287</span>&#160; R--;</div>
<div class="line"><a name="l00288"></a><span class="lineno"> 288</span>&#160; </div>
<div class="line"><a name="l00289"></a><span class="lineno"> 289</span>&#160; dmin /= num_samples;</div>
<div class="line"><a name="l00290"></a><span class="lineno"> 290</span>&#160; </div>
<div class="line"><a name="l00291"></a><span class="lineno"> 291</span>&#160; <span class="comment">// termination condition variable -&gt; % change in minimum distance</span></div>
<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>&#160; dmin_ratio = (past_dmin - dmin) / past_dmin;</div>
<div class="line"><a name="l00293"></a><span class="lineno"> 293</span>&#160; <span class="keywordflow">if</span> (dmin_ratio &lt; 0)</div>
<div class="line"><a name="l00294"></a><span class="lineno"> 294</span>&#160; dmin_ratio = 1.f;</div>
<div class="line"><a name="l00295"></a><span class="lineno"> 295</span>&#160; past_dmin = dmin;</div>
<div class="line"><a name="l00296"></a><span class="lineno"> 296</span>&#160; </div>
<div class="line"><a name="l00297"></a><span class="lineno"> 297</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;iter: &quot;</span> &lt;&lt; iter &lt;&lt; <span class="stringliteral">&quot;\t alpha: &quot;</span> &lt;&lt; alpha &lt;&lt; <span class="stringliteral">&quot;\t R: &quot;</span> &lt;&lt; R</div>
<div class="line"><a name="l00298"></a><span class="lineno"> 298</span>&#160; &lt;&lt; <span class="stringliteral">&quot;\t d_min: &quot;</span> &lt;&lt; dmin_ratio &lt;&lt; <span class="stringliteral">&quot;\r&quot;</span>;</div>
<div class="line"><a name="l00299"></a><span class="lineno"> 299</span>&#160; }</div>
<div class="line"><a name="l00300"></a><span class="lineno"> 300</span>&#160; </div>
<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a> &lt;&lt; <span class="stringliteral">&quot;\n&quot;</span>;</div>
<div class="line"><a name="l00302"></a><span class="lineno"> 302</span>&#160;}</div>
</div><!-- fragment --><div class="dynheader">
Here is the call graph for this function:</div>
<div class="dyncontent">
<div class="center"><div class="zoom"><iframe scrolling="no" frameborder="0" src="../../d8/d77/namespacemachine__learning_adc731720947b4bc2ab047c141e7d0299_cgraph.svg" width="100%" height="499"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe></div>
</div>
</div>
</div>
</div>
<a id="acc6a28f40512dbda75ab1a3969248898"></a>
<h2 class="memtitle"><span class="permalink"><a href="#acc6a28f40512dbda75ab1a3969248898">&#9670;&nbsp;</a></span>kohonen_som_tracer()</h2>
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">void machine_learning::kohonen_som_tracer </td>
<td>(</td>
<td class="paramtype">const <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt;&gt; &amp;&#160;</td>
<td class="paramname"><em>X</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt;&gt; *&#160;</td>
<td class="paramname"><em>W</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">double&#160;</td>
<td class="paramname"><em>alpha_min</em>&#160;</td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
</tr>
</table>
</div><div class="memdoc">
<p>Apply incremental algorithm with updating neighborhood and learning rates on all samples in the given datset.</p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">X</td><td>data set </td></tr>
<tr><td class="paramdir">[in,out]</td><td class="paramname">W</td><td>weights matrix </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">alpha_min</td><td>terminal value of alpha </td></tr>
</table>
</dd>
</dl>
<div class="fragment"><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; {</div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; <span class="keywordtype">int</span> num_samples = X.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>(); <span class="comment">// number of rows</span></div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; <span class="keywordtype">int</span> num_features = X[0].<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>(); <span class="comment">// number of columns</span></div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; <span class="keywordtype">int</span> num_out = W-&gt;<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>(); <span class="comment">// number of rows</span></div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; <span class="keywordtype">int</span> R = num_out &gt;&gt; 2, iter = 0;</div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; <span class="keywordtype">double</span> alpha = 1.f;</div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; </div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray&lt;double&gt;</a> D(num_out);</div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; </div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; <span class="comment">// Loop alpha from 1 to slpha_min</span></div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; <span class="keywordflow">for</span> (; alpha &gt; alpha_min; alpha -= 0.01, iter++) {</div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; <span class="comment">// Loop for each sample pattern in the data set</span></div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> sample = 0; sample &lt; num_samples; sample++) {</div>
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; <span class="comment">// update weights for the current input pattern sample</span></div>
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; <a class="code" href="../../d8/d77/namespacemachine__learning.html#a361674452869413536ee501f053129a8">update_weights</a>(X[sample], W, &amp;D, alpha, R);</div>
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; }</div>
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; </div>
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; <span class="comment">// every 10th iteration, reduce the neighborhood range</span></div>
<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160; <span class="keywordflow">if</span> (iter % 10 == 0 &amp;&amp; R &gt; 1)</div>
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160; R--;</div>
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160; }</div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160;}</div>
</div><!-- fragment --><div class="dynheader">
Here is the call graph for this function:</div>
<div class="dyncontent">
<div class="center"><div class="zoom"><iframe scrolling="no" frameborder="0" src="../../d8/d77/namespacemachine__learning_acc6a28f40512dbda75ab1a3969248898_cgraph.svg" width="100%" height="499"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe></div>
</div>
</div>
</div>
</div>
<a id="a1d577f5d95b774ae97eb6838852d0df5"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a1d577f5d95b774ae97eb6838852d0df5">&#9670;&nbsp;</a></span>save_u_matrix()</h2>
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">int machine_learning::save_u_matrix </td>
<td>(</td>
<td class="paramtype">const char *&#160;</td>
<td class="paramname"><em>fname</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt;&gt;&gt; &amp;&#160;</td>
<td class="paramname"><em>W</em>&#160;</td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
</tr>
</table>
</div><div class="memdoc">
<p>Create the distance matrix or <a href="https://en.wikipedia.org/wiki/U-matrix">U-matrix</a> from the trained 3D weiths matrix and save to disk.</p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">fname</td><td>filename to save in (gets overwriten without confirmation) </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">W</td><td>model matrix to save </td></tr>
</table>
</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>0 if all ok </dd>
<dd>
-1 if file creation failed </dd></dl>
<div class="fragment"><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; {</div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/basic_ofstream.html">std::ofstream</a> fp(fname);</div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; <span class="keywordflow">if</span> (!fp) { <span class="comment">// error with fopen</span></div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; <span class="keywordtype">char</span> msg[120];</div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/c/fprintf.html">std::snprintf</a>(msg, <span class="keyword">sizeof</span>(msg), <span class="stringliteral">&quot;File error (%s): &quot;</span>, fname);</div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/io/c/perror.html">std::perror</a>(msg);</div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; <span class="keywordflow">return</span> -1;</div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; }</div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; </div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; <span class="comment">// neighborhood range</span></div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> R = 1;</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; </div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; W.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>(); i++) { <span class="comment">// for each x</span></div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; W[0].<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>(); j++) { <span class="comment">// for each y</span></div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; <span class="keywordtype">double</span> <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/iterator/distance.html">distance</a> = 0.f;</div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; </div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; <span class="keywordtype">int</span> from_x = std::max&lt;int&gt;(0, i - R);</div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; <span class="keywordtype">int</span> to_x = std::min&lt;int&gt;(W.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>(), i + R + 1);</div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; <span class="keywordtype">int</span> from_y = std::max&lt;int&gt;(0, j - R);</div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; <span class="keywordtype">int</span> to_y = std::min&lt;int&gt;(W[0].size(), j + R + 1);</div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; <span class="keywordtype">int</span> l, m;</div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160;<span class="preprocessor">#pragma omp parallel for reduction(+ : distance)</span></div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; <span class="keywordflow">for</span> (l = from_x; l &lt; to_x; l++) { <span class="comment">// scan neighborhoor in x</span></div>
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; <span class="keywordflow">for</span> (m = from_y; m &lt; to_y; m++) { <span class="comment">// scan neighborhood in y</span></div>
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; <span class="keyword">auto</span> d = W[i][j] - W[l][m];</div>
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; <span class="keywordtype">double</span> d2 = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/math/pow.html">std::pow</a>(d, 2).sum();</div>
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/iterator/distance.html">distance</a> += <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/math/sqrt.html">std::sqrt</a>(d2);</div>
<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160; <span class="comment">// distance += d2;</span></div>
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160; }</div>
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160; }</div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160; </div>
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/iterator/distance.html">distance</a> /= R * R; <span class="comment">// mean distance from neighbors</span></div>
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160; fp &lt;&lt; <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/iterator/distance.html">distance</a>; <span class="comment">// print the mean separation</span></div>
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160; <span class="keywordflow">if</span> (j &lt; W[0].size() - 1) { <span class="comment">// if not the last column</span></div>
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160; fp &lt;&lt; <span class="charliteral">&#39;,&#39;</span>; <span class="comment">// suffix comma</span></div>
<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160; }</div>
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160; }</div>
<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160; <span class="keywordflow">if</span> (i &lt; W.<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>() - 1) <span class="comment">// if not the last row</span></div>
<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160; fp &lt;&lt; <span class="charliteral">&#39;\n&#39;</span>; <span class="comment">// start a new line</span></div>
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160; }</div>
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160; </div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160; fp.close();</div>
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160; <span class="keywordflow">return</span> 0;</div>
<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>&#160;}</div>
</div><!-- fragment --><div class="dynheader">
Here is the call graph for this function:</div>
<div class="dyncontent">
<div class="center"><iframe scrolling="no" frameborder="0" src="../../d8/d77/namespacemachine__learning_a1d577f5d95b774ae97eb6838852d0df5_cgraph.svg" width="356" height="240"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</div>
</div>
</div>
</div>
<a id="a361674452869413536ee501f053129a8"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a361674452869413536ee501f053129a8">&#9670;&nbsp;</a></span>update_weights() <span class="overload">[1/2]</span></h2>
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">void machine_learning::update_weights </td>
<td>(</td>
<td class="paramtype">const <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt; &amp;&#160;</td>
<td class="paramname"><em>x</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt;&gt; *&#160;</td>
<td class="paramname"><em>W</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt; *&#160;</td>
<td class="paramname"><em>D</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">double&#160;</td>
<td class="paramname"><em>alpha</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">int&#160;</td>
<td class="paramname"><em>R</em>&#160;</td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
</tr>
</table>
</div><div class="memdoc">
<p>Update weights of the SOM using Kohonen algorithm</p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">X</td><td>data point </td></tr>
<tr><td class="paramdir">[in,out]</td><td class="paramname">W</td><td>weights matrix </td></tr>
<tr><td class="paramdir">[in,out]</td><td class="paramname">D</td><td>temporary vector to store distances </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">alpha</td><td>learning rate \(0&lt;\alpha\le1\) </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">R</td><td>neighborhood range </td></tr>
</table>
</dd>
</dl>
<div class="fragment"><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; {</div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; <span class="keywordtype">int</span> j, k;</div>
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; <span class="keywordtype">int</span> num_out = W-&gt;<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>(); <span class="comment">// number of SOM output nodes</span></div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; <span class="keywordtype">int</span> num_features = x.size(); <span class="comment">// number of data features</span></div>
<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; </div>
<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160;<span class="preprocessor">#pragma omp for</span></div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; <span class="comment">// step 1: for each output point</span></div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; <span class="keywordflow">for</span> (j = 0; j &lt; num_out; j++) {</div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; <span class="comment">// compute Euclidian distance of each output</span></div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; <span class="comment">// point from the current sample</span></div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; (*D)[j] = (((*W)[j] - x) * ((*W)[j] - x)).sum();</div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; }</div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; </div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; <span class="comment">// step 2: get closest node i.e., node with snallest Euclidian distance to</span></div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; <span class="comment">// the current pattern</span></div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; <span class="keyword">auto</span> result = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/algorithm/min_element.html">std::min_element</a>(<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/iterator/begin.html">std::begin</a>(*D), <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/iterator/end.html">std::end</a>(*D));</div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; <span class="keywordtype">double</span> d_min = *result;</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; <span class="keywordtype">int</span> d_min_idx = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/iterator/distance.html">std::distance</a>(<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/iterator/begin.html">std::begin</a>(*D), result);</div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; </div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; <span class="comment">// step 3a: get the neighborhood range</span></div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; <span class="keywordtype">int</span> from_node = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/algorithm/max.html">std::max</a>(0, d_min_idx - R);</div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; <span class="keywordtype">int</span> to_node = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/algorithm/min.html">std::min</a>(num_out, d_min_idx + R + 1);</div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; </div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; <span class="comment">// step 3b: update the weights of nodes in the</span></div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; <span class="comment">// neighborhood</span></div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160;<span class="preprocessor">#pragma omp for</span></div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; <span class="keywordflow">for</span> (j = from_node; j &lt; to_node; j++)</div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; <span class="comment">// update weights of nodes in the neighborhood</span></div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; (*W)[j] += alpha * (x - (*W)[j]);</div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160;}</div>
</div><!-- fragment --><div class="dynheader">
Here is the call graph for this function:</div>
<div class="dyncontent">
<div class="center"><iframe scrolling="no" frameborder="0" src="../../d8/d77/namespacemachine__learning_a361674452869413536ee501f053129a8_cgraph.svg" width="352" height="291"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</div>
</div>
</div>
</div>
<a id="ac4010fe3a52a74e8b5b1aaadfe38b46f"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ac4010fe3a52a74e8b5b1aaadfe38b46f">&#9670;&nbsp;</a></span>update_weights() <span class="overload">[2/2]</span></h2>
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">double machine_learning::update_weights </td>
<td>(</td>
<td class="paramtype">const <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt; &amp;&#160;</td>
<td class="paramname"><em>X</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt;&gt;&gt; *&#160;</td>
<td class="paramname"><em>W</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a>&lt; <a class="elRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a>&lt; double &gt;&gt; *&#160;</td>
<td class="paramname"><em>D</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">double&#160;</td>
<td class="paramname"><em>alpha</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">int&#160;</td>
<td class="paramname"><em>R</em>&#160;</td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
</tr>
</table>
</div><div class="memdoc">
<p>Update weights of the SOM using Kohonen algorithm</p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">X</td><td>data point - N features </td></tr>
<tr><td class="paramdir">[in,out]</td><td class="paramname">W</td><td>weights matrix - PxQxN </td></tr>
<tr><td class="paramdir">[in,out]</td><td class="paramname">D</td><td>temporary vector to store distances PxQ </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">alpha</td><td>learning rate \(0&lt;\alpha\le1\) </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">R</td><td>neighborhood range </td></tr>
</table>
</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>minimum distance of sample and trained weights </dd></dl>
<div class="fragment"><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>&#160; {</div>
<div class="line"><a name="l00197"></a><span class="lineno"> 197</span>&#160; <span class="keywordtype">int</span> x, y;</div>
<div class="line"><a name="l00198"></a><span class="lineno"> 198</span>&#160; <span class="keywordtype">int</span> num_out_x = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(W-&gt;<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>()); <span class="comment">// output nodes - in X</span></div>
<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>&#160; <span class="keywordtype">int</span> num_out_y = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(W[0][0].<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>()); <span class="comment">// output nodes - in Y</span></div>
<div class="line"><a name="l00200"></a><span class="lineno"> 200</span>&#160; <span class="keywordtype">int</span> num_features = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(W[0][0][0].<a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/container/vector/size.html">size</a>()); <span class="comment">// features = in Z</span></div>
<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>&#160; <span class="keywordtype">double</span> d_min = 0.f;</div>
<div class="line"><a name="l00202"></a><span class="lineno"> 202</span>&#160; </div>
<div class="line"><a name="l00203"></a><span class="lineno"> 203</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00204"></a><span class="lineno"> 204</span>&#160;<span class="preprocessor">#pragma omp for</span></div>
<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>&#160; <span class="comment">// step 1: for each output point</span></div>
<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>&#160; <span class="keywordflow">for</span> (x = 0; x &lt; num_out_x; x++) {</div>
<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>&#160; <span class="keywordflow">for</span> (y = 0; y &lt; num_out_y; y++) {</div>
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span>&#160; (*D)[x][y] = 0.f;</div>
<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>&#160; <span class="comment">// compute Euclidian distance of each output</span></div>
<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>&#160; <span class="comment">// point from the current sample</span></div>
<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>&#160; <span class="keyword">auto</span> d = ((*W)[x][y] - X);</div>
<div class="line"><a name="l00213"></a><span class="lineno"> 213</span>&#160; (*D)[x][y] = (d * d).sum();</div>
<div class="line"><a name="l00214"></a><span class="lineno"> 214</span>&#160; (*D)[x][y] = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/math/sqrt.html">std::sqrt</a>((*D)[x][y]);</div>
<div class="line"><a name="l00215"></a><span class="lineno"> 215</span>&#160; }</div>
<div class="line"><a name="l00216"></a><span class="lineno"> 216</span>&#160; }</div>
<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>&#160; </div>
<div class="line"><a name="l00218"></a><span class="lineno"> 218</span>&#160; <span class="comment">// step 2: get closest node i.e., node with snallest Euclidian distance</span></div>
<div class="line"><a name="l00219"></a><span class="lineno"> 219</span>&#160; <span class="comment">// to the current pattern</span></div>
<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>&#160; <span class="keywordtype">int</span> d_min_x, d_min_y;</div>
<div class="line"><a name="l00221"></a><span class="lineno"> 221</span>&#160; <a class="code" href="../../d9/d66/group__machine__learning.html#gab53c14440b2b2dd3172c66afc5c2f63f">get_min_2d</a>(*D, &amp;d_min, &amp;d_min_x, &amp;d_min_y);</div>
<div class="line"><a name="l00222"></a><span class="lineno"> 222</span>&#160; </div>
<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>&#160; <span class="comment">// step 3a: get the neighborhood range</span></div>
<div class="line"><a name="l00224"></a><span class="lineno"> 224</span>&#160; <span class="keywordtype">int</span> from_x = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/algorithm/max.html">std::max</a>(0, d_min_x - R);</div>
<div class="line"><a name="l00225"></a><span class="lineno"> 225</span>&#160; <span class="keywordtype">int</span> to_x = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/algorithm/min.html">std::min</a>(num_out_x, d_min_x + R + 1);</div>
<div class="line"><a name="l00226"></a><span class="lineno"> 226</span>&#160; <span class="keywordtype">int</span> from_y = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/algorithm/max.html">std::max</a>(0, d_min_y - R);</div>
<div class="line"><a name="l00227"></a><span class="lineno"> 227</span>&#160; <span class="keywordtype">int</span> to_y = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/algorithm/min.html">std::min</a>(num_out_y, d_min_y + R + 1);</div>
<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>&#160; </div>
<div class="line"><a name="l00229"></a><span class="lineno"> 229</span>&#160; <span class="comment">// step 3b: update the weights of nodes in the</span></div>
<div class="line"><a name="l00230"></a><span class="lineno"> 230</span>&#160; <span class="comment">// neighborhood</span></div>
<div class="line"><a name="l00231"></a><span class="lineno"> 231</span>&#160;<span class="preprocessor">#ifdef _OPENMP</span></div>
<div class="line"><a name="l00232"></a><span class="lineno"> 232</span>&#160;<span class="preprocessor">#pragma omp for</span></div>
<div class="line"><a name="l00233"></a><span class="lineno"> 233</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>&#160; <span class="keywordflow">for</span> (x = from_x; x &lt; to_x; x++) {</div>
<div class="line"><a name="l00235"></a><span class="lineno"> 235</span>&#160; <span class="keywordflow">for</span> (y = from_y; y &lt; to_y; y++) {</div>
<div class="line"><a name="l00236"></a><span class="lineno"> 236</span>&#160; <span class="comment">/* you can enable the following normalization if needed.</span></div>
<div class="line"><a name="l00237"></a><span class="lineno"> 237</span>&#160;<span class="comment"> personally, I found it detrimental to convergence */</span></div>
<div class="line"><a name="l00238"></a><span class="lineno"> 238</span>&#160; <span class="comment">// const double s2pi = sqrt(2.f * M_PI);</span></div>
<div class="line"><a name="l00239"></a><span class="lineno"> 239</span>&#160; <span class="comment">// double normalize = 1.f / (alpha * s2pi);</span></div>
<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>&#160; </div>
<div class="line"><a name="l00241"></a><span class="lineno"> 241</span>&#160; <span class="comment">/* apply scaling inversely proportional to distance from the</span></div>
<div class="line"><a name="l00242"></a><span class="lineno"> 242</span>&#160;<span class="comment"> current node */</span></div>
<div class="line"><a name="l00243"></a><span class="lineno"> 243</span>&#160; <span class="keywordtype">double</span> d2 =</div>
<div class="line"><a name="l00244"></a><span class="lineno"> 244</span>&#160; (d_min_x - x) * (d_min_x - x) + (d_min_y - y) * (d_min_y - y);</div>
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>&#160; <span class="keywordtype">double</span> scale_factor = <a class="codeRef" target="_blank" href="http://en.cppreference.com/w/cpp/numeric/math/exp.html">std::exp</a>(-d2 / (2.f * alpha * alpha));</div>
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>&#160; </div>
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span>&#160; (*W)[x][y] += (X - (*W)[x][y]) * alpha * scale_factor;</div>
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span>&#160; }</div>
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>&#160; }</div>
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>&#160; <span class="keywordflow">return</span> d_min;</div>
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>&#160;}</div>
</div><!-- fragment --><div class="dynheader">
Here is the call graph for this function:</div>
<div class="dyncontent">
<div class="center"><iframe scrolling="no" frameborder="0" src="../../d8/d77/namespacemachine__learning_ac4010fe3a52a74e8b5b1aaadfe38b46f_cgraph.svg" width="490" height="266"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</div>
</div>
</div>
</div>
</div><!-- contents -->
</div><!-- doc-content -->
<div class="ttc" id="anamespacemachine__learning_html_a361674452869413536ee501f053129a8"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#a361674452869413536ee501f053129a8">machine_learning::update_weights</a></div><div class="ttdeci">void update_weights(const std::valarray&lt; double &gt; &amp;x, std::vector&lt; std::valarray&lt; double &gt;&gt; *W, std::valarray&lt; double &gt; *D, double alpha, int R)</div><div class="ttdef"><b>Definition:</b> kohonen_som_trace.cpp:100</div></div>
<div class="ttc" id="avector_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/container/vector.html">std::vector</a></div><div class="ttdoc">STL class.</div></div>
<div class="ttc" id="asize_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/container/vector/size.html">std::vector::size</a></div><div class="ttdeci">T size(T... args)</div></div>
<div class="ttc" id="adistance_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/iterator/distance.html">std::distance</a></div><div class="ttdeci">T distance(T... args)</div></div>
<div class="ttc" id="anamespacemachine__learning_html_ac4010fe3a52a74e8b5b1aaadfe38b46f"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#ac4010fe3a52a74e8b5b1aaadfe38b46f">machine_learning::update_weights</a></div><div class="ttdeci">double update_weights(const std::valarray&lt; double &gt; &amp;X, std::vector&lt; std::vector&lt; std::valarray&lt; double &gt;&gt;&gt; *W, std::vector&lt; std::valarray&lt; double &gt;&gt; *D, double alpha, int R)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:193</div></div>
<div class="ttc" id="agroup__machine__learning_html_gab53c14440b2b2dd3172c66afc5c2f63f"><div class="ttname"><a href="../../d9/d66/group__machine__learning.html#gab53c14440b2b2dd3172c66afc5c2f63f">get_min_2d</a></div><div class="ttdeci">void get_min_2d(const std::vector&lt; std::valarray&lt; double &gt;&gt; &amp;X, double *val, int *x_idx, int *y_idx)</div><div class="ttdef"><b>Definition:</b> kohonen_som_topology.cpp:99</div></div>
<div class="ttc" id="asqrt_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/numeric/math/sqrt.html">std::sqrt</a></div><div class="ttdeci">T sqrt(T... args)</div></div>
<div class="ttc" id="afprintf_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/io/c/fprintf.html">std::snprintf</a></div><div class="ttdeci">T snprintf(T... args)</div></div>
<div class="ttc" id="abasic_ostream_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/io/basic_ostream.html">std::cout</a></div></div>
<div class="ttc" id="abasic_ofstream_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/io/basic_ofstream.html">std::ofstream</a></div><div class="ttdoc">STL class.</div></div>
<div class="ttc" id="amin_element_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/algorithm/min_element.html">std::min_element</a></div><div class="ttdeci">T min_element(T... args)</div></div>
<div class="ttc" id="aperror_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/io/c/perror.html">std::perror</a></div><div class="ttdeci">T perror(T... args)</div></div>
<div class="ttc" id="avalarray_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/numeric/valarray.html">std::valarray</a></div><div class="ttdoc">STL class.</div></div>
<div class="ttc" id="amin_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/algorithm/min.html">std::min</a></div><div class="ttdeci">T min(T... args)</div></div>
<div class="ttc" id="aexp_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/numeric/math/exp.html">std::exp</a></div><div class="ttdeci">T exp(T... args)</div></div>
<div class="ttc" id="abegin_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/iterator/begin.html">std::begin</a></div><div class="ttdeci">T begin(T... args)</div></div>
<div class="ttc" id="aend_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/iterator/end.html">std::end</a></div><div class="ttdeci">T end(T... args)</div></div>
<div class="ttc" id="amax_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/algorithm/max.html">std::max</a></div><div class="ttdeci">T max(T... args)</div></div>
<div class="ttc" id="apow_html"><div class="ttname"><a href="http://en.cppreference.com/w/cpp/numeric/math/pow.html">std::pow</a></div><div class="ttdeci">T pow(T... args)</div></div>
<!-- start footer part -->
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="../../d8/d77/namespacemachine__learning.html">machine_learning</a></li>
<li class="footer">Generated by
<a href="http://www.doxygen.org/index.html">
<img class="footer" src="../../doxygen.png" alt="doxygen"/></a> 1.8.18 </li>
</ul>
</div>
</body>
</html>
Reference in New Issue View Git Blame Copy Permalink