mirror of
https://github.com/TheAlgorithms/C-Plus-Plus.git
synced 2026-03-22 04:42:10 +08:00
657 lines
47 KiB
HTML
657 lines
47 KiB
HTML
<!-- HTML header for doxygen 1.12.0-->
|
|
<!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" lang="en-US">
|
|
<head>
|
|
<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/>
|
|
<meta http-equiv="X-UA-Compatible" content="IE=11"/>
|
|
<meta name="generator" content="Doxygen 1.13.2"/>
|
|
<meta name="viewport" content="width=device-width, initial-scale=1"/>
|
|
<title>TheAlgorithms/C++: adaline Class Reference</title>
|
|
<link rel="icon" href="../../favicon.svg" type="image/x-icon" />
|
|
<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>
|
|
<script type="text/javascript" src="https://cdn.jsdelivr.net/npm/@xpack-3rd-party/doxygen-awesome-css@2.2.0-1/doxygen-awesome-darkmode-toggle.js"></script>
|
|
<script type="text/javascript">
|
|
DoxygenAwesomeDarkModeToggle.init()
|
|
</script>
|
|
<script type="text/javascript" src="../../clipboard.js"></script>
|
|
<link href="../../navtree.css" rel="stylesheet" type="text/css"/>
|
|
<script type="text/javascript" src="../../navtreedata.js"></script>
|
|
<script type="text/javascript" src="../../navtree.js"></script>
|
|
<script type="text/javascript" src="../../resize.js"></script>
|
|
<script type="text/javascript" src="../../cookie.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/javascript">
|
|
window.MathJax = {
|
|
options: {
|
|
ignoreHtmlClass: 'tex2jax_ignore',
|
|
processHtmlClass: 'tex2jax_process'
|
|
},
|
|
loader: {
|
|
load: ['[tex]/ams']
|
|
},
|
|
tex: {
|
|
macros: {},
|
|
packages: ['base','configmacros','ams']
|
|
}
|
|
};
|
|
</script>
|
|
<script type="text/javascript" id="MathJax-script" async="async" src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-chtml.js"></script>
|
|
<link href="../../doxygen.css" rel="stylesheet" type="text/css" />
|
|
<link href="../../doxygen-awesome.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 id="projectrow">
|
|
<td id="projectlogo"><img alt="Logo" src="../../project_logo.png"/></td>
|
|
<td id="projectalign">
|
|
<div id="projectname">TheAlgorithms/C++<span id="projectnumber"> 1.0.0</span>
|
|
</div>
|
|
<div id="projectbrief">All the algorithms implemented in C++</div>
|
|
</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
</div>
|
|
<!-- end header part -->
|
|
<!-- Generated by Doxygen 1.13.2 -->
|
|
<script type="text/javascript">
|
|
/* @license magnet:?xt=urn:btih:d3d9a9a6595521f9666a5e94cc830dab83b65699&dn=expat.txt MIT */
|
|
var searchBox = new SearchBox("searchBox", "../../search/",'.html');
|
|
/* @license-end */
|
|
</script>
|
|
<script type="text/javascript">
|
|
/* @license magnet:?xt=urn:btih:d3d9a9a6595521f9666a5e94cc830dab83b65699&dn=expat.txt MIT */
|
|
$(function() { codefold.init(1); });
|
|
/* @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:d3d9a9a6595521f9666a5e94cc830dab83b65699&dn=expat.txt MIT */
|
|
$(function() {
|
|
initMenu('../../',true,false,'search.php','Search',true);
|
|
$(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:d3d9a9a6595521f9666a5e94cc830dab83b65699&dn=expat.txt MIT */
|
|
$(function(){initNavTree('d8/df2/classadaline.html','../../'); initResizable(true); });
|
|
/* @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">
|
|
<div id="MSearchResults">
|
|
<div class="SRPage">
|
|
<div id="SRIndex">
|
|
<div id="SRResults"></div>
|
|
<div class="SRStatus" id="Loading">Loading...</div>
|
|
<div class="SRStatus" id="Searching">Searching...</div>
|
|
<div class="SRStatus" id="NoMatches">No Matches</div>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
<div class="header">
|
|
<div class="summary">
|
|
<a href="#pub-methods">Public Member Functions</a> |
|
|
<a href="#pri-methods">Private Member Functions</a> |
|
|
<a href="#pri-attribs">Private Attributes</a> |
|
|
<a href="#friends">Friends</a> |
|
|
<a href="../../d5/d84/classadaline-members.html">List of all members</a> </div>
|
|
<div class="headertitle"><div class="title">adaline Class Reference</div></div>
|
|
</div><!--header-->
|
|
<div class="contents">
|
|
<div class="dynheader">
|
|
Collaboration diagram for adaline:</div>
|
|
<div class="dyncontent">
|
|
<div class="center"><iframe scrolling="no" frameborder="0" src="../../d2/d77/classadaline__coll__graph.svg" width="156" height="126"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe></div>
|
|
<center><span class="legend">[<a target="top" href="../../graph_legend.html">legend</a>]</span></center></div>
|
|
<table class="memberdecls">
|
|
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a id="pub-methods" name="pub-methods"></a>
|
|
Public Member Functions</h2></td></tr>
|
|
<tr class="memitem:a0acbe32aaab897e7939e5b0454035b8c" id="r_a0acbe32aaab897e7939e5b0454035b8c"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="#a0acbe32aaab897e7939e5b0454035b8c">adaline</a> (int num_features, const double <a class="el" href="#a28160d17e492597a2f112e0d38551cda">eta</a>=0.01f, const double <a class="el" href="#aa23d60262f917f35836ef4b1c1d9f7d3">accuracy</a>=1e-5)</td></tr>
|
|
<tr class="separator:a0acbe32aaab897e7939e5b0454035b8c"><td class="memSeparator" colspan="2"> </td></tr>
|
|
<tr class="memitem:ab11242d9ad5b03a75911e29b04f78fd3" id="r_ab11242d9ad5b03a75911e29b04f78fd3"><td class="memItemLeft" align="right" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="#ab11242d9ad5b03a75911e29b04f78fd3">predict</a> (const std::vector< double > &x, double *out=nullptr)</td></tr>
|
|
<tr class="separator:ab11242d9ad5b03a75911e29b04f78fd3"><td class="memSeparator" colspan="2"> </td></tr>
|
|
<tr class="memitem:a74e3c6c037b67895014414c5d75465e5" id="r_a74e3c6c037b67895014414c5d75465e5"><td class="memItemLeft" align="right" valign="top">double </td><td class="memItemRight" valign="bottom"><a class="el" href="#a74e3c6c037b67895014414c5d75465e5">fit</a> (const std::vector< double > &x, const int &y)</td></tr>
|
|
<tr class="separator:a74e3c6c037b67895014414c5d75465e5"><td class="memSeparator" colspan="2"> </td></tr>
|
|
<tr class="memitem:a8d61f9ed872eef26bca39388cbda6a91" id="r_a8d61f9ed872eef26bca39388cbda6a91"><td class="memTemplParams" colspan="2">template<size_t N> </td></tr>
|
|
<tr class="memitem:a8d61f9ed872eef26bca39388cbda6a91"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="#a8d61f9ed872eef26bca39388cbda6a91">fit</a> (std::array< std::vector< double >, N > const &X, std::array< int, N > const &Y)</td></tr>
|
|
<tr class="separator:a8d61f9ed872eef26bca39388cbda6a91"><td class="memSeparator" colspan="2"> </td></tr>
|
|
<tr class="memitem:a082f758fb55fe19f22b3df66f89b2325" id="r_a082f758fb55fe19f22b3df66f89b2325"><td class="memItemLeft" align="right" valign="top">int </td><td class="memItemRight" valign="bottom"><a class="el" href="#a082f758fb55fe19f22b3df66f89b2325">activation</a> (double x)</td></tr>
|
|
<tr class="separator:a082f758fb55fe19f22b3df66f89b2325"><td class="memSeparator" colspan="2"> </td></tr>
|
|
</table><table class="memberdecls">
|
|
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a id="pri-methods" name="pri-methods"></a>
|
|
Private Member Functions</h2></td></tr>
|
|
<tr class="memitem:ac8a9c2aaaa63b0f27ea176857e1e7d56" id="r_ac8a9c2aaaa63b0f27ea176857e1e7d56"><td class="memItemLeft" align="right" valign="top">bool </td><td class="memItemRight" valign="bottom"><a class="el" href="#ac8a9c2aaaa63b0f27ea176857e1e7d56">check_size_match</a> (const std::vector< double > &x)</td></tr>
|
|
<tr class="separator:ac8a9c2aaaa63b0f27ea176857e1e7d56"><td class="memSeparator" colspan="2"> </td></tr>
|
|
</table><table class="memberdecls">
|
|
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a id="pri-attribs" name="pri-attribs"></a>
|
|
Private Attributes</h2></td></tr>
|
|
<tr class="memitem:a28160d17e492597a2f112e0d38551cda" id="r_a28160d17e492597a2f112e0d38551cda"><td class="memItemLeft" align="right" valign="top">const double </td><td class="memItemRight" valign="bottom"><a class="el" href="#a28160d17e492597a2f112e0d38551cda">eta</a></td></tr>
|
|
<tr class="memdesc:a28160d17e492597a2f112e0d38551cda"><td class="mdescLeft"> </td><td class="mdescRight">learning rate of the algorithm <br /></td></tr>
|
|
<tr class="separator:a28160d17e492597a2f112e0d38551cda"><td class="memSeparator" colspan="2"> </td></tr>
|
|
<tr class="memitem:aa23d60262f917f35836ef4b1c1d9f7d3" id="r_aa23d60262f917f35836ef4b1c1d9f7d3"><td class="memItemLeft" align="right" valign="top">const double </td><td class="memItemRight" valign="bottom"><a class="el" href="#aa23d60262f917f35836ef4b1c1d9f7d3">accuracy</a></td></tr>
|
|
<tr class="memdesc:aa23d60262f917f35836ef4b1c1d9f7d3"><td class="mdescLeft"> </td><td class="mdescRight">model fit convergence accuracy <br /></td></tr>
|
|
<tr class="separator:aa23d60262f917f35836ef4b1c1d9f7d3"><td class="memSeparator" colspan="2"> </td></tr>
|
|
<tr class="memitem:a4cd8fe438032fedaa66f93bfd66f5492" id="r_a4cd8fe438032fedaa66f93bfd66f5492"><td class="memItemLeft" align="right" valign="top">std::vector< double > </td><td class="memItemRight" valign="bottom"><a class="el" href="#a4cd8fe438032fedaa66f93bfd66f5492">weights</a></td></tr>
|
|
<tr class="memdesc:a4cd8fe438032fedaa66f93bfd66f5492"><td class="mdescLeft"> </td><td class="mdescRight">weights of the neural network <br /></td></tr>
|
|
<tr class="separator:a4cd8fe438032fedaa66f93bfd66f5492"><td class="memSeparator" colspan="2"> </td></tr>
|
|
</table><table class="memberdecls">
|
|
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a id="friends" name="friends"></a>
|
|
Friends</h2></td></tr>
|
|
<tr class="memitem:ae347040516e995c8fb8ca2e5c0496daa" id="r_ae347040516e995c8fb8ca2e5c0496daa"><td class="memItemLeft" align="right" valign="top">std::ostream & </td><td class="memItemRight" valign="bottom"><a class="el" href="#ae347040516e995c8fb8ca2e5c0496daa">operator<<</a> (std::ostream &out, const <a class="el" href="../../d6/d30/classmachine__learning_1_1adaline.html">adaline</a> &ada)</td></tr>
|
|
<tr class="separator:ae347040516e995c8fb8ca2e5c0496daa"><td class="memSeparator" colspan="2"> </td></tr>
|
|
</table>
|
|
<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
|
|
<div class="textblock">
|
|
<p class="definition">Definition at line <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html#l00046">46</a> of file <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html">adaline_learning.cpp</a>.</p>
|
|
</div><h2 class="groupheader">Constructor & Destructor Documentation</h2>
|
|
<a id="a0acbe32aaab897e7939e5b0454035b8c" name="a0acbe32aaab897e7939e5b0454035b8c"></a>
|
|
<h2 class="memtitle"><span class="permalink"><a href="#a0acbe32aaab897e7939e5b0454035b8c">◆ </a></span>adaline()</h2>
|
|
|
|
<div class="memitem">
|
|
<div class="memproto">
|
|
<table class="mlabels">
|
|
<tr>
|
|
<td class="mlabels-left">
|
|
<table class="memname">
|
|
<tr>
|
|
<td class="memname">machine_learning::adaline::adaline </td>
|
|
<td>(</td>
|
|
<td class="paramtype">int</td> <td class="paramname"><span class="paramname"><em>num_features</em></span>, </td>
|
|
</tr>
|
|
<tr>
|
|
<td class="paramkey"></td>
|
|
<td></td>
|
|
<td class="paramtype">const double</td> <td class="paramname"><span class="paramname"><em>eta</em></span><span class="paramdefsep"> = </span><span class="paramdefval">0.01f</span>, </td>
|
|
</tr>
|
|
<tr>
|
|
<td class="paramkey"></td>
|
|
<td></td>
|
|
<td class="paramtype">const double</td> <td class="paramname"><span class="paramname"><em>accuracy</em></span><span class="paramdefsep"> = </span><span class="paramdefval">1e-5</span> )</td>
|
|
</tr>
|
|
</table>
|
|
</td>
|
|
<td class="mlabels-right">
|
|
<span class="mlabels"><span class="mlabel inline">inline</span><span class="mlabel explicit">explicit</span></span> </td>
|
|
</tr>
|
|
</table>
|
|
</div><div class="memdoc">
|
|
<p>Default constructor </p><dl class="params"><dt>Parameters</dt><dd>
|
|
<table class="params">
|
|
<tr><td class="paramdir">[in]</td><td class="paramname">num_features</td><td>number of features present </td></tr>
|
|
<tr><td class="paramdir">[in]</td><td class="paramname">eta</td><td>learning rate (optional, default=0.1) </td></tr>
|
|
<tr><td class="paramdir">[in]</td><td class="paramname">convergence</td><td>accuracy (optional, default= \(1\times10^{-5}\)) </td></tr>
|
|
</table>
|
|
</dd>
|
|
</dl>
|
|
|
|
<p class="definition">Definition at line <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html#l00055">55</a> of file <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html">adaline_learning.cpp</a>.</p>
|
|
<div class="fragment"><div class="line"><span class="lineno"> 57</span> : <a class="code hl_variable" href="../../d6/d30/classmachine__learning_1_1adaline.html#a28160d17e492597a2f112e0d38551cda">eta</a>(<a class="code hl_variable" href="#a28160d17e492597a2f112e0d38551cda">eta</a>), <a class="code hl_variable" href="../../d6/d30/classmachine__learning_1_1adaline.html#aa23d60262f917f35836ef4b1c1d9f7d3">accuracy</a>(<a class="code hl_variable" href="#aa23d60262f917f35836ef4b1c1d9f7d3">accuracy</a>) {</div>
|
|
<div class="line"><span class="lineno"> 58</span> <span class="keywordflow">if</span> (<a class="code hl_variable" href="#a28160d17e492597a2f112e0d38551cda">eta</a> <= 0) {</div>
|
|
<div class="line"><span class="lineno"> 59</span> std::cerr << <span class="stringliteral">"learning rate should be positive and nonzero"</span></div>
|
|
<div class="line"><span class="lineno"> 60</span> << std::endl;</div>
|
|
<div class="line"><span class="lineno"> 61</span> std::exit(EXIT_FAILURE);</div>
|
|
<div class="line"><span class="lineno"> 62</span> }</div>
|
|
<div class="line"><span class="lineno"> 63</span> </div>
|
|
<div class="line"><span class="lineno"> 64</span> <a class="code hl_variable" href="#a4cd8fe438032fedaa66f93bfd66f5492">weights</a> = std::vector<double>(</div>
|
|
<div class="line"><span class="lineno"> 65</span> num_features +</div>
|
|
<div class="line"><span class="lineno"> 66</span> 1); <span class="comment">// additional weight is for the constant bias term</span></div>
|
|
<div class="line"><span class="lineno"> 67</span> </div>
|
|
<div class="line"><span class="lineno"> 68</span> <span class="comment">// initialize with random weights in the range [-50, 49]</span></div>
|
|
<div class="line"><span class="lineno"> 69</span> <span class="keywordflow">for</span> (<span class="keywordtype">double</span> &weight : <a class="code hl_variable" href="#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>) weight = 1.f;</div>
|
|
<div class="line"><span class="lineno"> 70</span> <span class="comment">// weights[i] = (static_cast<double>(std::rand() % 100) - 50);</span></div>
|
|
<div class="line"><span class="lineno"> 71</span> }</div>
|
|
<div class="ttc" id="aclassadaline_html_a28160d17e492597a2f112e0d38551cda"><div class="ttname"><a href="#a28160d17e492597a2f112e0d38551cda">adaline::eta</a></div><div class="ttdeci">const double eta</div><div class="ttdoc">learning rate of the algorithm</div><div class="ttdef"><b>Definition</b> <a href="../../d5/db0/adaline__learning_8cpp_source.html#l00207">adaline_learning.cpp:207</a></div></div>
|
|
<div class="ttc" id="aclassadaline_html_a4cd8fe438032fedaa66f93bfd66f5492"><div class="ttname"><a href="#a4cd8fe438032fedaa66f93bfd66f5492">adaline::weights</a></div><div class="ttdeci">std::vector< double > weights</div><div class="ttdoc">weights of the neural network</div><div class="ttdef"><b>Definition</b> <a href="../../d5/db0/adaline__learning_8cpp_source.html#l00209">adaline_learning.cpp:209</a></div></div>
|
|
<div class="ttc" id="aclassadaline_html_aa23d60262f917f35836ef4b1c1d9f7d3"><div class="ttname"><a href="#aa23d60262f917f35836ef4b1c1d9f7d3">adaline::accuracy</a></div><div class="ttdeci">const double accuracy</div><div class="ttdoc">model fit convergence accuracy</div><div class="ttdef"><b>Definition</b> <a href="../../d5/db0/adaline__learning_8cpp_source.html#l00208">adaline_learning.cpp:208</a></div></div>
|
|
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_a28160d17e492597a2f112e0d38551cda"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#a28160d17e492597a2f112e0d38551cda">machine_learning::adaline::eta</a></div><div class="ttdeci">const double eta</div><div class="ttdoc">learning rate of the algorithm</div><div class="ttdef"><b>Definition</b> <a href="../../d5/db0/adaline__learning_8cpp_source.html#l00207">adaline_learning.cpp:207</a></div></div>
|
|
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_aa23d60262f917f35836ef4b1c1d9f7d3"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#aa23d60262f917f35836ef4b1c1d9f7d3">machine_learning::adaline::accuracy</a></div><div class="ttdeci">const double accuracy</div><div class="ttdoc">model fit convergence accuracy</div><div class="ttdef"><b>Definition</b> <a href="../../d5/db0/adaline__learning_8cpp_source.html#l00208">adaline_learning.cpp:208</a></div></div>
|
|
</div><!-- fragment -->
|
|
</div>
|
|
</div>
|
|
<h2 class="groupheader">Member Function Documentation</h2>
|
|
<a id="a082f758fb55fe19f22b3df66f89b2325" name="a082f758fb55fe19f22b3df66f89b2325"></a>
|
|
<h2 class="memtitle"><span class="permalink"><a href="#a082f758fb55fe19f22b3df66f89b2325">◆ </a></span>activation()</h2>
|
|
|
|
<div class="memitem">
|
|
<div class="memproto">
|
|
<table class="mlabels">
|
|
<tr>
|
|
<td class="mlabels-left">
|
|
<table class="memname">
|
|
<tr>
|
|
<td class="memname">int machine_learning::adaline::activation </td>
|
|
<td>(</td>
|
|
<td class="paramtype">double</td> <td class="paramname"><span class="paramname"><em>x</em></span></td><td>)</td>
|
|
<td></td>
|
|
</tr>
|
|
</table>
|
|
</td>
|
|
<td class="mlabels-right">
|
|
<span class="mlabels"><span class="mlabel inline">inline</span></span> </td>
|
|
</tr>
|
|
</table>
|
|
</div><div class="memdoc">
|
|
<p>Defines activation function as Heaviside's step function. </p><p class="formulaDsp">
|
|
\[f(x) = \begin{cases}
|
|
-1 & \forall x \le 0\\
|
|
1 & \forall x > 0
|
|
\end{cases}
|
|
\]
|
|
</p>
|
|
<dl class="params"><dt>Parameters</dt><dd>
|
|
<table class="params">
|
|
<tr><td class="paramname">x</td><td>input value to apply activation on </td></tr>
|
|
</table>
|
|
</dd>
|
|
</dl>
|
|
<dl class="section return"><dt>Returns</dt><dd>activation output </dd></dl>
|
|
|
|
<p class="definition">Definition at line <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html#l00186">186</a> of file <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html">adaline_learning.cpp</a>.</p>
|
|
<div class="fragment"><div class="line"><span class="lineno"> 186</span>{ <span class="keywordflow">return</span> x > 0 ? 1 : -1; }</div>
|
|
</div><!-- fragment -->
|
|
</div>
|
|
</div>
|
|
<a id="ac8a9c2aaaa63b0f27ea176857e1e7d56" name="ac8a9c2aaaa63b0f27ea176857e1e7d56"></a>
|
|
<h2 class="memtitle"><span class="permalink"><a href="#ac8a9c2aaaa63b0f27ea176857e1e7d56">◆ </a></span>check_size_match()</h2>
|
|
|
|
<div class="memitem">
|
|
<div class="memproto">
|
|
<table class="mlabels">
|
|
<tr>
|
|
<td class="mlabels-left">
|
|
<table class="memname">
|
|
<tr>
|
|
<td class="memname">bool machine_learning::adaline::check_size_match </td>
|
|
<td>(</td>
|
|
<td class="paramtype">const std::vector< double > &</td> <td class="paramname"><span class="paramname"><em>x</em></span></td><td>)</td>
|
|
<td></td>
|
|
</tr>
|
|
</table>
|
|
</td>
|
|
<td class="mlabels-right">
|
|
<span class="mlabels"><span class="mlabel inline">inline</span><span class="mlabel private">private</span></span> </td>
|
|
</tr>
|
|
</table>
|
|
</div><div class="memdoc">
|
|
<p>convenient function to check if input feature vector size matches the model weights size </p><dl class="params"><dt>Parameters</dt><dd>
|
|
<table class="params">
|
|
<tr><td class="paramdir">[in]</td><td class="paramname">x</td><td>fecture vector to check </td></tr>
|
|
</table>
|
|
</dd>
|
|
</dl>
|
|
<dl class="section return"><dt>Returns</dt><dd><code>true</code> size matches </dd>
|
|
<dd>
|
|
<code>false</code> size does not match </dd></dl>
|
|
|
|
<p class="definition">Definition at line <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html#l00196">196</a> of file <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html">adaline_learning.cpp</a>.</p>
|
|
<div class="fragment"><div class="line"><span class="lineno"> 196</span> {</div>
|
|
<div class="line"><span class="lineno"> 197</span> <span class="keywordflow">if</span> (x.size() != (<a class="code hl_variable" href="#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>.size() - 1)) {</div>
|
|
<div class="line"><span class="lineno"> 198</span> std::cerr << __func__ << <span class="stringliteral">": "</span></div>
|
|
<div class="line"><span class="lineno"> 199</span> << <span class="stringliteral">"Number of features in x does not match the feature "</span></div>
|
|
<div class="line"><span class="lineno"> 200</span> <span class="stringliteral">"dimension in model!"</span></div>
|
|
<div class="line"><span class="lineno"> 201</span> << std::endl;</div>
|
|
<div class="line"><span class="lineno"> 202</span> <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
|
|
<div class="line"><span class="lineno"> 203</span> }</div>
|
|
<div class="line"><span class="lineno"> 204</span> <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
|
|
<div class="line"><span class="lineno"> 205</span> }</div>
|
|
</div><!-- fragment -->
|
|
</div>
|
|
</div>
|
|
<a id="a74e3c6c037b67895014414c5d75465e5" name="a74e3c6c037b67895014414c5d75465e5"></a>
|
|
<h2 class="memtitle"><span class="permalink"><a href="#a74e3c6c037b67895014414c5d75465e5">◆ </a></span>fit() <span class="overload">[1/2]</span></h2>
|
|
|
|
<div class="memitem">
|
|
<div class="memproto">
|
|
<table class="mlabels">
|
|
<tr>
|
|
<td class="mlabels-left">
|
|
<table class="memname">
|
|
<tr>
|
|
<td class="memname">double machine_learning::adaline::fit </td>
|
|
<td>(</td>
|
|
<td class="paramtype">const std::vector< double > &</td> <td class="paramname"><span class="paramname"><em>x</em></span>, </td>
|
|
</tr>
|
|
<tr>
|
|
<td class="paramkey"></td>
|
|
<td></td>
|
|
<td class="paramtype">const int &</td> <td class="paramname"><span class="paramname"><em>y</em></span> )</td>
|
|
</tr>
|
|
</table>
|
|
</td>
|
|
<td class="mlabels-right">
|
|
<span class="mlabels"><span class="mlabel inline">inline</span></span> </td>
|
|
</tr>
|
|
</table>
|
|
</div><div class="memdoc">
|
|
<p>Update the weights of the model using supervised learning for one feature vector </p><dl class="params"><dt>Parameters</dt><dd>
|
|
<table class="params">
|
|
<tr><td class="paramdir">[in]</td><td class="paramname">x</td><td>feature vector </td></tr>
|
|
<tr><td class="paramdir">[in]</td><td class="paramname">y</td><td>known output value </td></tr>
|
|
</table>
|
|
</dd>
|
|
</dl>
|
|
<dl class="section return"><dt>Returns</dt><dd>correction factor </dd></dl>
|
|
|
|
<p class="definition">Definition at line <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html#l00119">119</a> of file <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html">adaline_learning.cpp</a>.</p>
|
|
<div class="fragment"><div class="line"><span class="lineno"> 119</span> {</div>
|
|
<div class="line"><span class="lineno"> 120</span> <span class="keywordflow">if</span> (!<a class="code hl_function" href="../../d6/d30/classmachine__learning_1_1adaline.html#ac8a9c2aaaa63b0f27ea176857e1e7d56">check_size_match</a>(x)) {</div>
|
|
<div class="line"><span class="lineno"> 121</span> <span class="keywordflow">return</span> 0;</div>
|
|
<div class="line"><span class="lineno"> 122</span> }</div>
|
|
<div class="line"><span class="lineno"> 123</span> </div>
|
|
<div class="line"><span class="lineno"> 124</span> <span class="comment">/* output of the model with current weights */</span></div>
|
|
<div class="line"><span class="lineno"> 125</span> <span class="keywordtype">int</span> p = <a class="code hl_function" href="../../d6/d30/classmachine__learning_1_1adaline.html#ab11242d9ad5b03a75911e29b04f78fd3">predict</a>(x);</div>
|
|
<div class="line"><span class="lineno"> 126</span> <span class="keywordtype">int</span> prediction_error = y - p; <span class="comment">// error in estimation</span></div>
|
|
<div class="line"><span class="lineno"> 127</span> <span class="keywordtype">double</span> correction_factor = <a class="code hl_variable" href="#a28160d17e492597a2f112e0d38551cda">eta</a> * prediction_error;</div>
|
|
<div class="line"><span class="lineno"> 128</span> </div>
|
|
<div class="line"><span class="lineno"> 129</span> <span class="comment">/* update each weight, the last weight is the bias term */</span></div>
|
|
<div class="line"><span class="lineno"> 130</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < x.size(); i++) {</div>
|
|
<div class="line"><span class="lineno"> 131</span> <a class="code hl_variable" href="#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>[i] += correction_factor * x[i];</div>
|
|
<div class="line"><span class="lineno"> 132</span> }</div>
|
|
<div class="line"><span class="lineno"> 133</span> <a class="code hl_variable" href="#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>[x.size()] += correction_factor; <span class="comment">// update bias</span></div>
|
|
<div class="line"><span class="lineno"> 134</span> </div>
|
|
<div class="line"><span class="lineno"> 135</span> <span class="keywordflow">return</span> correction_factor;</div>
|
|
<div class="line"><span class="lineno"> 136</span> }</div>
|
|
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_ab11242d9ad5b03a75911e29b04f78fd3"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#ab11242d9ad5b03a75911e29b04f78fd3">machine_learning::adaline::predict</a></div><div class="ttdeci">int predict(const std::vector< double > &x, double *out=nullptr)</div><div class="ttdef"><b>Definition</b> <a href="../../d5/db0/adaline__learning_8cpp_source.html#l00095">adaline_learning.cpp:95</a></div></div>
|
|
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_ac8a9c2aaaa63b0f27ea176857e1e7d56"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#ac8a9c2aaaa63b0f27ea176857e1e7d56">machine_learning::adaline::check_size_match</a></div><div class="ttdeci">bool check_size_match(const std::vector< double > &x)</div><div class="ttdef"><b>Definition</b> <a href="../../d5/db0/adaline__learning_8cpp_source.html#l00196">adaline_learning.cpp:196</a></div></div>
|
|
</div><!-- fragment -->
|
|
</div>
|
|
</div>
|
|
<a id="a8d61f9ed872eef26bca39388cbda6a91" name="a8d61f9ed872eef26bca39388cbda6a91"></a>
|
|
<h2 class="memtitle"><span class="permalink"><a href="#a8d61f9ed872eef26bca39388cbda6a91">◆ </a></span>fit() <span class="overload">[2/2]</span></h2>
|
|
|
|
<div class="memitem">
|
|
<div class="memproto">
|
|
<div class="memtemplate">
|
|
template<size_t N> </div>
|
|
<table class="mlabels">
|
|
<tr>
|
|
<td class="mlabels-left">
|
|
<table class="memname">
|
|
<tr>
|
|
<td class="memname">void machine_learning::adaline::fit </td>
|
|
<td>(</td>
|
|
<td class="paramtype">std::array< std::vector< double >, N > const &</td> <td class="paramname"><span class="paramname"><em>X</em></span>, </td>
|
|
</tr>
|
|
<tr>
|
|
<td class="paramkey"></td>
|
|
<td></td>
|
|
<td class="paramtype">std::array< int, N > const &</td> <td class="paramname"><span class="paramname"><em>Y</em></span> )</td>
|
|
</tr>
|
|
</table>
|
|
</td>
|
|
<td class="mlabels-right">
|
|
<span class="mlabels"><span class="mlabel inline">inline</span></span> </td>
|
|
</tr>
|
|
</table>
|
|
</div><div class="memdoc">
|
|
<p>Update the weights of the model using supervised learning for an array of vectors. </p><dl class="params"><dt>Parameters</dt><dd>
|
|
<table class="params">
|
|
<tr><td class="paramdir">[in]</td><td class="paramname">X</td><td>array of feature vector </td></tr>
|
|
<tr><td class="paramdir">[in]</td><td class="paramname">y</td><td>known output value for each feature vector </td></tr>
|
|
</table>
|
|
</dd>
|
|
</dl>
|
|
|
|
<p class="definition">Definition at line <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html#l00145">145</a> of file <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html">adaline_learning.cpp</a>.</p>
|
|
<div class="fragment"><div class="line"><span class="lineno"> 146</span> {</div>
|
|
<div class="line"><span class="lineno"> 147</span> <span class="keywordtype">double</span> avg_pred_error = 1.f;</div>
|
|
<div class="line"><span class="lineno"> 148</span> </div>
|
|
<div class="line"><span class="lineno"> 149</span> <span class="keywordtype">int</span> iter = 0;</div>
|
|
<div class="line"><span class="lineno"> 150</span> <span class="keywordflow">for</span> (iter = 0; (iter < <a class="code hl_variable" href="../../d9/d66/group__machine__learning.html#ga5118e5cbc4f0886e27b3a7a2544dded1">MAX_ITER</a>) && (avg_pred_error > <a class="code hl_variable" href="#aa23d60262f917f35836ef4b1c1d9f7d3">accuracy</a>);</div>
|
|
<div class="line"><span class="lineno"> 151</span> iter++) {</div>
|
|
<div class="line"><span class="lineno"> 152</span> avg_pred_error = 0.f;</div>
|
|
<div class="line"><span class="lineno"> 153</span> </div>
|
|
<div class="line"><span class="lineno"> 154</span> <span class="comment">// perform fit for each sample</span></div>
|
|
<div class="line"><span class="lineno"> 155</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < <a class="code hl_variable" href="../../d8/dab/sparse__table_8cpp.html#a10f3ffb3f6f7e1b83d556b9c8de89a5d">N</a>; i++) {</div>
|
|
<div class="line"><span class="lineno"> 156</span> <span class="keywordtype">double</span> err = <a class="code hl_function" href="../../d6/d30/classmachine__learning_1_1adaline.html#a74e3c6c037b67895014414c5d75465e5">fit</a>(X[i], Y[i]);</div>
|
|
<div class="line"><span class="lineno"> 157</span> avg_pred_error += std::abs(err);</div>
|
|
<div class="line"><span class="lineno"> 158</span> }</div>
|
|
<div class="line"><span class="lineno"> 159</span> avg_pred_error /= <a class="code hl_variable" href="../../d8/dab/sparse__table_8cpp.html#a10f3ffb3f6f7e1b83d556b9c8de89a5d">N</a>;</div>
|
|
<div class="line"><span class="lineno"> 160</span> </div>
|
|
<div class="line"><span class="lineno"> 161</span> <span class="comment">// Print updates every 200th iteration</span></div>
|
|
<div class="line"><span class="lineno"> 162</span> <span class="comment">// if (iter % 100 == 0)</span></div>
|
|
<div class="line"><span class="lineno"> 163</span> std::cout << <span class="stringliteral">"\tIter "</span> << iter << <span class="stringliteral">": Training weights: "</span> << *<span class="keyword">this</span></div>
|
|
<div class="line"><span class="lineno"> 164</span> << <span class="stringliteral">"\tAvg error: "</span> << avg_pred_error << std::endl;</div>
|
|
<div class="line"><span class="lineno"> 165</span> }</div>
|
|
<div class="line"><span class="lineno"> 166</span> </div>
|
|
<div class="line"><span class="lineno"> 167</span> <span class="keywordflow">if</span> (iter < <a class="code hl_variable" href="../../d9/d66/group__machine__learning.html#ga5118e5cbc4f0886e27b3a7a2544dded1">MAX_ITER</a>) {</div>
|
|
<div class="line"><span class="lineno"> 168</span> std::cout << <span class="stringliteral">"Converged after "</span> << iter << <span class="stringliteral">" iterations."</span></div>
|
|
<div class="line"><span class="lineno"> 169</span> << std::endl;</div>
|
|
<div class="line"><span class="lineno"> 170</span> } <span class="keywordflow">else</span> {</div>
|
|
<div class="line"><span class="lineno"> 171</span> std::cout << <span class="stringliteral">"Did not converge after "</span> << iter << <span class="stringliteral">" iterations."</span></div>
|
|
<div class="line"><span class="lineno"> 172</span> << std::endl;</div>
|
|
<div class="line"><span class="lineno"> 173</span> }</div>
|
|
<div class="line"><span class="lineno"> 174</span> }</div>
|
|
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_a74e3c6c037b67895014414c5d75465e5"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#a74e3c6c037b67895014414c5d75465e5">machine_learning::adaline::fit</a></div><div class="ttdeci">double fit(const std::vector< double > &x, const int &y)</div><div class="ttdef"><b>Definition</b> <a href="../../d5/db0/adaline__learning_8cpp_source.html#l00119">adaline_learning.cpp:119</a></div></div>
|
|
<div class="ttc" id="agroup__machine__learning_html_ga5118e5cbc4f0886e27b3a7a2544dded1"><div class="ttname"><a href="../../d9/d66/group__machine__learning.html#ga5118e5cbc4f0886e27b3a7a2544dded1">MAX_ITER</a></div><div class="ttdeci">constexpr int MAX_ITER</div><div class="ttdef"><b>Definition</b> <a href="../../d5/db0/adaline__learning_8cpp_source.html#l00040">adaline_learning.cpp:40</a></div></div>
|
|
<div class="ttc" id="asparse__table_8cpp_html_a10f3ffb3f6f7e1b83d556b9c8de89a5d"><div class="ttname"><a href="../../d8/dab/sparse__table_8cpp.html#a10f3ffb3f6f7e1b83d556b9c8de89a5d">data_structures::sparse_table::N</a></div><div class="ttdeci">constexpr uint32_t N</div><div class="ttdoc">A struct to represent sparse table for min() as their invariant function, for the given array A....</div><div class="ttdef"><b>Definition</b> <a href="../../d8/dab/sparse__table_8cpp_source.html#l00048">sparse_table.cpp:48</a></div></div>
|
|
</div><!-- fragment -->
|
|
</div>
|
|
</div>
|
|
<a id="ab11242d9ad5b03a75911e29b04f78fd3" name="ab11242d9ad5b03a75911e29b04f78fd3"></a>
|
|
<h2 class="memtitle"><span class="permalink"><a href="#ab11242d9ad5b03a75911e29b04f78fd3">◆ </a></span>predict()</h2>
|
|
|
|
<div class="memitem">
|
|
<div class="memproto">
|
|
<table class="mlabels">
|
|
<tr>
|
|
<td class="mlabels-left">
|
|
<table class="memname">
|
|
<tr>
|
|
<td class="memname">int machine_learning::adaline::predict </td>
|
|
<td>(</td>
|
|
<td class="paramtype">const std::vector< double > &</td> <td class="paramname"><span class="paramname"><em>x</em></span>, </td>
|
|
</tr>
|
|
<tr>
|
|
<td class="paramkey"></td>
|
|
<td></td>
|
|
<td class="paramtype">double *</td> <td class="paramname"><span class="paramname"><em>out</em></span><span class="paramdefsep"> = </span><span class="paramdefval">nullptr</span> )</td>
|
|
</tr>
|
|
</table>
|
|
</td>
|
|
<td class="mlabels-right">
|
|
<span class="mlabels"><span class="mlabel inline">inline</span></span> </td>
|
|
</tr>
|
|
</table>
|
|
</div><div class="memdoc">
|
|
<p>predict the output of the model for given set of features </p><dl class="params"><dt>Parameters</dt><dd>
|
|
<table class="params">
|
|
<tr><td class="paramdir">[in]</td><td class="paramname">x</td><td>input vector </td></tr>
|
|
<tr><td class="paramdir">[out]</td><td class="paramname">out</td><td>optional argument to return neuron output before applying activation function (optional, <code>nullptr</code> to ignore) </td></tr>
|
|
</table>
|
|
</dd>
|
|
</dl>
|
|
<dl class="section return"><dt>Returns</dt><dd>model prediction output </dd></dl>
|
|
|
|
<p class="definition">Definition at line <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html#l00095">95</a> of file <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html">adaline_learning.cpp</a>.</p>
|
|
<div class="fragment"><div class="line"><span class="lineno"> 95</span> {</div>
|
|
<div class="line"><span class="lineno"> 96</span> <span class="keywordflow">if</span> (!<a class="code hl_function" href="../../d6/d30/classmachine__learning_1_1adaline.html#ac8a9c2aaaa63b0f27ea176857e1e7d56">check_size_match</a>(x)) {</div>
|
|
<div class="line"><span class="lineno"> 97</span> <span class="keywordflow">return</span> 0;</div>
|
|
<div class="line"><span class="lineno"> 98</span> }</div>
|
|
<div class="line"><span class="lineno"> 99</span> </div>
|
|
<div class="line"><span class="lineno"> 100</span> <span class="keywordtype">double</span> y = <a class="code hl_variable" href="#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>.back(); <span class="comment">// assign bias value</span></div>
|
|
<div class="line"><span class="lineno"> 101</span> </div>
|
|
<div class="line"><span class="lineno"> 102</span> <span class="comment">// for (int i = 0; i < x.size(); i++) y += x[i] * weights[i];</span></div>
|
|
<div class="line"><span class="lineno"> 103</span> y = std::inner_product(x.begin(), x.end(), <a class="code hl_variable" href="#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>.begin(), y);</div>
|
|
<div class="line"><span class="lineno"> 104</span> </div>
|
|
<div class="line"><span class="lineno"> 105</span> <span class="keywordflow">if</span> (out != <span class="keyword">nullptr</span>) { <span class="comment">// if out variable is provided</span></div>
|
|
<div class="line"><span class="lineno"> 106</span> *out = y;</div>
|
|
<div class="line"><span class="lineno"> 107</span> }</div>
|
|
<div class="line"><span class="lineno"> 108</span> </div>
|
|
<div class="line"><span class="lineno"> 109</span> <span class="keywordflow">return</span> <a class="code hl_function" href="../../d6/d30/classmachine__learning_1_1adaline.html#a082f758fb55fe19f22b3df66f89b2325">activation</a>(y); <span class="comment">// quantizer: apply ADALINE threshold function</span></div>
|
|
<div class="line"><span class="lineno"> 110</span> }</div>
|
|
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_a082f758fb55fe19f22b3df66f89b2325"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#a082f758fb55fe19f22b3df66f89b2325">machine_learning::adaline::activation</a></div><div class="ttdeci">int activation(double x)</div><div class="ttdef"><b>Definition</b> <a href="../../d5/db0/adaline__learning_8cpp_source.html#l00186">adaline_learning.cpp:186</a></div></div>
|
|
</div><!-- fragment -->
|
|
</div>
|
|
</div>
|
|
<h2 class="groupheader">Friends And Related Symbol Documentation</h2>
|
|
<a id="ae347040516e995c8fb8ca2e5c0496daa" name="ae347040516e995c8fb8ca2e5c0496daa"></a>
|
|
<h2 class="memtitle"><span class="permalink"><a href="#ae347040516e995c8fb8ca2e5c0496daa">◆ </a></span>operator<<</h2>
|
|
|
|
<div class="memitem">
|
|
<div class="memproto">
|
|
<table class="mlabels">
|
|
<tr>
|
|
<td class="mlabels-left">
|
|
<table class="memname">
|
|
<tr>
|
|
<td class="memname">std::ostream & operator<< </td>
|
|
<td>(</td>
|
|
<td class="paramtype">std::ostream &</td> <td class="paramname"><span class="paramname"><em>out</em></span>, </td>
|
|
</tr>
|
|
<tr>
|
|
<td class="paramkey"></td>
|
|
<td></td>
|
|
<td class="paramtype">const <a class="el" href="../../d6/d30/classmachine__learning_1_1adaline.html">adaline</a> &</td> <td class="paramname"><span class="paramname"><em>ada</em></span> )</td>
|
|
</tr>
|
|
</table>
|
|
</td>
|
|
<td class="mlabels-right">
|
|
<span class="mlabels"><span class="mlabel friend">friend</span></span> </td>
|
|
</tr>
|
|
</table>
|
|
</div><div class="memdoc">
|
|
<p>Operator to print the weights of the model </p>
|
|
|
|
<p class="definition">Definition at line <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html#l00076">76</a> of file <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html">adaline_learning.cpp</a>.</p>
|
|
<div class="fragment"><div class="line"><span class="lineno"> 76</span> {</div>
|
|
<div class="line"><span class="lineno"> 77</span> out << <span class="stringliteral">"<"</span>;</div>
|
|
<div class="line"><span class="lineno"> 78</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < ada.<a class="code hl_variable" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>.size(); i++) {</div>
|
|
<div class="line"><span class="lineno"> 79</span> out << ada.<a class="code hl_variable" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>[i];</div>
|
|
<div class="line"><span class="lineno"> 80</span> <span class="keywordflow">if</span> (i < ada.<a class="code hl_variable" href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">weights</a>.size() - 1) {</div>
|
|
<div class="line"><span class="lineno"> 81</span> out << <span class="stringliteral">", "</span>;</div>
|
|
<div class="line"><span class="lineno"> 82</span> }</div>
|
|
<div class="line"><span class="lineno"> 83</span> }</div>
|
|
<div class="line"><span class="lineno"> 84</span> out << <span class="stringliteral">">"</span>;</div>
|
|
<div class="line"><span class="lineno"> 85</span> <span class="keywordflow">return</span> out;</div>
|
|
<div class="line"><span class="lineno"> 86</span> }</div>
|
|
<div class="ttc" id="aclassmachine__learning_1_1adaline_html_a4cd8fe438032fedaa66f93bfd66f5492"><div class="ttname"><a href="../../d6/d30/classmachine__learning_1_1adaline.html#a4cd8fe438032fedaa66f93bfd66f5492">machine_learning::adaline::weights</a></div><div class="ttdeci">std::vector< double > weights</div><div class="ttdoc">weights of the neural network</div><div class="ttdef"><b>Definition</b> <a href="../../d5/db0/adaline__learning_8cpp_source.html#l00209">adaline_learning.cpp:209</a></div></div>
|
|
</div><!-- fragment -->
|
|
</div>
|
|
</div>
|
|
<h2 class="groupheader">Member Data Documentation</h2>
|
|
<a id="aa23d60262f917f35836ef4b1c1d9f7d3" name="aa23d60262f917f35836ef4b1c1d9f7d3"></a>
|
|
<h2 class="memtitle"><span class="permalink"><a href="#aa23d60262f917f35836ef4b1c1d9f7d3">◆ </a></span>accuracy</h2>
|
|
|
|
<div class="memitem">
|
|
<div class="memproto">
|
|
<table class="mlabels">
|
|
<tr>
|
|
<td class="mlabels-left">
|
|
<table class="memname">
|
|
<tr>
|
|
<td class="memname">const double machine_learning::adaline::accuracy</td>
|
|
</tr>
|
|
</table>
|
|
</td>
|
|
<td class="mlabels-right">
|
|
<span class="mlabels"><span class="mlabel private">private</span></span> </td>
|
|
</tr>
|
|
</table>
|
|
</div><div class="memdoc">
|
|
|
|
<p>model fit convergence accuracy </p>
|
|
|
|
<p class="definition">Definition at line <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html#l00208">208</a> of file <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html">adaline_learning.cpp</a>.</p>
|
|
|
|
</div>
|
|
</div>
|
|
<a id="a28160d17e492597a2f112e0d38551cda" name="a28160d17e492597a2f112e0d38551cda"></a>
|
|
<h2 class="memtitle"><span class="permalink"><a href="#a28160d17e492597a2f112e0d38551cda">◆ </a></span>eta</h2>
|
|
|
|
<div class="memitem">
|
|
<div class="memproto">
|
|
<table class="mlabels">
|
|
<tr>
|
|
<td class="mlabels-left">
|
|
<table class="memname">
|
|
<tr>
|
|
<td class="memname">const double machine_learning::adaline::eta</td>
|
|
</tr>
|
|
</table>
|
|
</td>
|
|
<td class="mlabels-right">
|
|
<span class="mlabels"><span class="mlabel private">private</span></span> </td>
|
|
</tr>
|
|
</table>
|
|
</div><div class="memdoc">
|
|
|
|
<p>learning rate of the algorithm </p>
|
|
|
|
<p class="definition">Definition at line <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html#l00207">207</a> of file <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html">adaline_learning.cpp</a>.</p>
|
|
|
|
</div>
|
|
</div>
|
|
<a id="a4cd8fe438032fedaa66f93bfd66f5492" name="a4cd8fe438032fedaa66f93bfd66f5492"></a>
|
|
<h2 class="memtitle"><span class="permalink"><a href="#a4cd8fe438032fedaa66f93bfd66f5492">◆ </a></span>weights</h2>
|
|
|
|
<div class="memitem">
|
|
<div class="memproto">
|
|
<table class="mlabels">
|
|
<tr>
|
|
<td class="mlabels-left">
|
|
<table class="memname">
|
|
<tr>
|
|
<td class="memname">std::vector<double> machine_learning::adaline::weights</td>
|
|
</tr>
|
|
</table>
|
|
</td>
|
|
<td class="mlabels-right">
|
|
<span class="mlabels"><span class="mlabel private">private</span></span> </td>
|
|
</tr>
|
|
</table>
|
|
</div><div class="memdoc">
|
|
|
|
<p>weights of the neural network </p>
|
|
|
|
<p class="definition">Definition at line <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html#l00209">209</a> of file <a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html">adaline_learning.cpp</a>.</p>
|
|
|
|
</div>
|
|
</div>
|
|
<hr/>The documentation for this class was generated from the following file:<ul>
|
|
<li>machine_learning/<a class="el" href="../../d5/db0/adaline__learning_8cpp_source.html">adaline_learning.cpp</a></li>
|
|
</ul>
|
|
</div><!-- contents -->
|
|
</div><!-- doc-content -->
|
|
<!-- start footer part -->
|
|
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
|
|
<ul>
|
|
<li class="navelem"><a class="el" href="../../d8/df2/classadaline.html">adaline</a></li>
|
|
<li class="footer">Generated by <a href="https://www.doxygen.org/index.html"><img class="footer" src="../../doxygen.svg" width="104" height="31" alt="doxygen"/></a> 1.13.2 </li>
|
|
</ul>
|
|
</div>
|
|
</body>
|
|
</html>
|