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<div class="title">em_fit.hpp</div> </div>
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<a href="em__fit_8hpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> </div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#ifndef MLPACK_METHODS_GMM_EM_FIT_HPP</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#define MLPACK_METHODS_GMM_EM_FIT_HPP</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> </div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="preprocessor">#include <<a class="code" href="prereqs_8hpp.html">mlpack/prereqs.hpp</a>></span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor">#include <<a class="code" href="gaussian__distribution_8hpp.html">mlpack/core/dists/gaussian_distribution.hpp</a>></span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> </div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="comment">// Default clustering mechanism.</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="preprocessor">#include <<a class="code" href="kmeans_8hpp.html">mlpack/methods/kmeans/kmeans.hpp</a>></span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="comment">// Default covariance matrix constraint.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="preprocessor">#include "<a class="code" href="positive__definite__constraint_8hpp.html">positive_definite_constraint.hpp</a>"</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> </div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="keyword">namespace </span><a class="code" href="namespacemlpack.html">mlpack</a> {</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="keyword">namespace </span>gmm {</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> </div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="keyword">template</span><<span class="keyword">typename</span> InitialClusteringType = kmeans::KMeans<>,</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keyword">typename</span> CovarianceConstra<span class="keywordtype">int</span>Policy = PositiveDefiniteConstra<span class="keywordtype">int</span>></div><div class="line"><a name="l00043"></a><span class="lineno"><a class="line" href="classmlpack_1_1gmm_1_1EMFit.html"> 43</a></span> <span class="keyword">class </span><a class="code" href="classmlpack_1_1gmm_1_1EMFit.html">EMFit</a></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> {</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keyword">public</span>:</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#a629f0c991f79d2baa3fb09c49ba3834f">EMFit</a>(<span class="keyword">const</span> <span class="keywordtype">size_t</span> <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#a7cec14ec7765af815fe30e3899c6812c">maxIterations</a> = 300,</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="keyword">const</span> <span class="keywordtype">double</span> <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#aa068530ec69e3fc9b329f68adb6f6716">tolerance</a> = 1e-10,</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  InitialClusteringType <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#ae2c22954de90170cb1f96e36d35fcf5e">clusterer</a> = InitialClusteringType(),</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  CovarianceConstraintPolicy <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#a7dceacbb8ad05fa9ffca11dac4a1e372">constraint</a> = CovarianceConstraintPolicy());</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> </div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keywordtype">void</span> <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#a866986fd0df110ec1b32d25d71ac6a23">Estimate</a>(<span class="keyword">const</span> arma::mat& observations,</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  std::vector<distribution::GaussianDistribution>& dists,</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  arma::vec& weights,</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> useInitialModel = <span class="keyword">false</span>);</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> </div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="keywordtype">void</span> <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#a866986fd0df110ec1b32d25d71ac6a23">Estimate</a>(<span class="keyword">const</span> arma::mat& observations,</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keyword">const</span> arma::vec& probabilities,</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  std::vector<distribution::GaussianDistribution>& dists,</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  arma::vec& weights,</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> useInitialModel = <span class="keyword">false</span>);</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> </div><div class="line"><a name="l00112"></a><span class="lineno"><a class="line" href="classmlpack_1_1gmm_1_1EMFit.html#a9552740fd3dd1625320b402e5773b17d"> 112</a></span>  <span class="keyword">const</span> InitialClusteringType& <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#a9552740fd3dd1625320b402e5773b17d">Clusterer</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#ae2c22954de90170cb1f96e36d35fcf5e">clusterer</a>; }</div><div class="line"><a name="l00114"></a><span class="lineno"><a class="line" href="classmlpack_1_1gmm_1_1EMFit.html#a707dba7c98fcf7cc828bdef8e6d299d1"> 114</a></span>  InitialClusteringType& <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#a707dba7c98fcf7cc828bdef8e6d299d1">Clusterer</a>() { <span class="keywordflow">return</span> <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#ae2c22954de90170cb1f96e36d35fcf5e">clusterer</a>; }</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> </div><div class="line"><a name="l00117"></a><span class="lineno"><a class="line" href="classmlpack_1_1gmm_1_1EMFit.html#a3837a426192b5aa6583c780efc7964cb"> 117</a></span>  <span class="keyword">const</span> CovarianceConstraintPolicy& <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#a3837a426192b5aa6583c780efc7964cb">Constraint</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#a7dceacbb8ad05fa9ffca11dac4a1e372">constraint</a>; }</div><div class="line"><a name="l00119"></a><span class="lineno"><a class="line" href="classmlpack_1_1gmm_1_1EMFit.html#abd646e32dea239c90f312fe0f29b0abf"> 119</a></span>  CovarianceConstraintPolicy& <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#abd646e32dea239c90f312fe0f29b0abf">Constraint</a>() { <span class="keywordflow">return</span> <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#a7dceacbb8ad05fa9ffca11dac4a1e372">constraint</a>; }</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> </div><div class="line"><a name="l00122"></a><span class="lineno"><a class="line" href="classmlpack_1_1gmm_1_1EMFit.html#af6c593e716a094b742d2d157f52ca75e"> 122</a></span>  <span class="keywordtype">size_t</span> <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#af6c593e716a094b742d2d157f52ca75e">MaxIterations</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#a7cec14ec7765af815fe30e3899c6812c">maxIterations</a>; }</div><div class="line"><a name="l00124"></a><span class="lineno"><a class="line" href="classmlpack_1_1gmm_1_1EMFit.html#ab1d0543bde9b1a4f2431e599a4470d93"> 124</a></span>  <span class="keywordtype">size_t</span>& <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#ab1d0543bde9b1a4f2431e599a4470d93">MaxIterations</a>() { <span class="keywordflow">return</span> <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#a7cec14ec7765af815fe30e3899c6812c">maxIterations</a>; }</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> </div><div class="line"><a name="l00127"></a><span class="lineno"><a class="line" href="classmlpack_1_1gmm_1_1EMFit.html#aa3aad8721a7e8538ea9c3cdacc35a996"> 127</a></span>  <span class="keywordtype">double</span> <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#aa3aad8721a7e8538ea9c3cdacc35a996">Tolerance</a>()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#aa068530ec69e3fc9b329f68adb6f6716">tolerance</a>; }</div><div class="line"><a name="l00129"></a><span class="lineno"><a class="line" href="classmlpack_1_1gmm_1_1EMFit.html#a9bdffd46ef67bec866e5819fdc56bf2b"> 129</a></span>  <span class="keywordtype">double</span>& <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#a9bdffd46ef67bec866e5819fdc56bf2b">Tolerance</a>() { <span class="keywordflow">return</span> <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#aa068530ec69e3fc9b329f68adb6f6716">tolerance</a>; }</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> </div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="keyword">template</span><<span class="keyword">typename</span> Archive></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="keywordtype">void</span> <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#a86bf5dcce8f31358af461ad78f055b37">Serialize</a>(Archive& ar, <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> version);</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> </div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <span class="keyword">private</span>:</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="keywordtype">void</span> <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#ae9d13d0112224ce200118d85cc1f4856">InitialClustering</a>(<span class="keyword">const</span> arma::mat& observations,</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  std::vector<distribution::GaussianDistribution>& dists,</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  arma::vec& weights);</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> </div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keywordtype">double</span> <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#a331b4e87ccd48fb56019cfd039c7d266">LogLikelihood</a>(<span class="keyword">const</span> arma::mat& data,</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  <span class="keyword">const</span> std::vector<distribution::GaussianDistribution>&</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  dists,</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <span class="keyword">const</span> arma::vec& weights) <span class="keyword">const</span>;</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> </div><div class="line"><a name="l00166"></a><span class="lineno"><a class="line" href="classmlpack_1_1gmm_1_1EMFit.html#a7cec14ec7765af815fe30e3899c6812c"> 166</a></span>  <span class="keywordtype">size_t</span> <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#a7cec14ec7765af815fe30e3899c6812c">maxIterations</a>;</div><div class="line"><a name="l00168"></a><span class="lineno"><a class="line" href="classmlpack_1_1gmm_1_1EMFit.html#aa068530ec69e3fc9b329f68adb6f6716"> 168</a></span>  <span class="keywordtype">double</span> <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#aa068530ec69e3fc9b329f68adb6f6716">tolerance</a>;</div><div class="line"><a name="l00170"></a><span class="lineno"><a class="line" href="classmlpack_1_1gmm_1_1EMFit.html#ae2c22954de90170cb1f96e36d35fcf5e"> 170</a></span>  InitialClusteringType <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#ae2c22954de90170cb1f96e36d35fcf5e">clusterer</a>;</div><div class="line"><a name="l00172"></a><span class="lineno"><a class="line" href="classmlpack_1_1gmm_1_1EMFit.html#a7dceacbb8ad05fa9ffca11dac4a1e372"> 172</a></span>  CovarianceConstraintPolicy <a class="code" href="classmlpack_1_1gmm_1_1EMFit.html#a7dceacbb8ad05fa9ffca11dac4a1e372">constraint</a>;</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span> };</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span> </div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span> } <span class="comment">// namespace gmm</span></div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span> } <span class="comment">// namespace mlpack</span></div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span> </div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span> <span class="comment">// Include implementation.</span></div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span> <span class="preprocessor">#include "em_fit_impl.hpp"</span></div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span> </div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span> <span class="preprocessor">#endif</span></div><div class="ttc" id="classmlpack_1_1gmm_1_1EMFit_html"><div class="ttname"><a href="classmlpack_1_1gmm_1_1EMFit.html">mlpack::gmm::EMFit</a></div><div class="ttdoc">This class contains methods which can fit a GMM to observations using the EM algorithm. </div><div class="ttdef"><b>Definition:</b> <a href="em__fit_8hpp_source.html#l00043">em_fit.hpp:43</a></div></div>
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<div class="ttc" id="classmlpack_1_1gmm_1_1EMFit_html_a866986fd0df110ec1b32d25d71ac6a23"><div class="ttname"><a href="classmlpack_1_1gmm_1_1EMFit.html#a866986fd0df110ec1b32d25d71ac6a23">mlpack::gmm::EMFit::Estimate</a></div><div class="ttdeci">void Estimate(const arma::mat &observations, std::vector< distribution::GaussianDistribution > &dists, arma::vec &weights, const bool useInitialModel=false)</div><div class="ttdoc">Fit the observations to a Gaussian mixture model (GMM) using the EM algorithm. </div></div>
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<div class="ttc" id="classmlpack_1_1gmm_1_1EMFit_html_a331b4e87ccd48fb56019cfd039c7d266"><div class="ttname"><a href="classmlpack_1_1gmm_1_1EMFit.html#a331b4e87ccd48fb56019cfd039c7d266">mlpack::gmm::EMFit::LogLikelihood</a></div><div class="ttdeci">double LogLikelihood(const arma::mat &data, const std::vector< distribution::GaussianDistribution > &dists, const arma::vec &weights) const </div><div class="ttdoc">Calculate the log-likelihood of a model. </div></div>
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<div class="ttc" id="gaussian__distribution_8hpp_html"><div class="ttname"><a href="gaussian__distribution_8hpp.html">gaussian_distribution.hpp</a></div></div>
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<div class="ttc" id="classmlpack_1_1gmm_1_1EMFit_html_a9bdffd46ef67bec866e5819fdc56bf2b"><div class="ttname"><a href="classmlpack_1_1gmm_1_1EMFit.html#a9bdffd46ef67bec866e5819fdc56bf2b">mlpack::gmm::EMFit::Tolerance</a></div><div class="ttdeci">double & Tolerance()</div><div class="ttdoc">Modify the tolerance for the convergence of the EM algorithm. </div><div class="ttdef"><b>Definition:</b> <a href="em__fit_8hpp_source.html#l00129">em_fit.hpp:129</a></div></div>
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<div class="ttc" id="classmlpack_1_1gmm_1_1EMFit_html_a3837a426192b5aa6583c780efc7964cb"><div class="ttname"><a href="classmlpack_1_1gmm_1_1EMFit.html#a3837a426192b5aa6583c780efc7964cb">mlpack::gmm::EMFit::Constraint</a></div><div class="ttdeci">const CovarianceConstraintPolicy & Constraint() const </div><div class="ttdoc">Get the covariance constraint policy class. </div><div class="ttdef"><b>Definition:</b> <a href="em__fit_8hpp_source.html#l00117">em_fit.hpp:117</a></div></div>
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<div class="ttc" id="namespacemlpack_html"><div class="ttname"><a href="namespacemlpack.html">mlpack</a></div><div class="ttdoc">Linear algebra utility functions, generally performed on matrices or vectors. </div><div class="ttdef"><b>Definition:</b> <a href="binarize_8hpp_source.html#l00018">binarize.hpp:18</a></div></div>
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<div class="ttc" id="classmlpack_1_1gmm_1_1EMFit_html_ae9d13d0112224ce200118d85cc1f4856"><div class="ttname"><a href="classmlpack_1_1gmm_1_1EMFit.html#ae9d13d0112224ce200118d85cc1f4856">mlpack::gmm::EMFit::InitialClustering</a></div><div class="ttdeci">void InitialClustering(const arma::mat &observations, std::vector< distribution::GaussianDistribution > &dists, arma::vec &weights)</div><div class="ttdoc">Run the clusterer, and then turn the cluster assignments into Gaussians. </div></div>
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<div class="ttc" id="prereqs_8hpp_html"><div class="ttname"><a href="prereqs_8hpp.html">prereqs.hpp</a></div><div class="ttdoc">The core includes that mlpack expects; standard C++ includes and Armadillo. </div></div>
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<div class="ttc" id="positive__definite__constraint_8hpp_html"><div class="ttname"><a href="positive__definite__constraint_8hpp.html">positive_definite_constraint.hpp</a></div></div>
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<div class="ttc" id="classmlpack_1_1gmm_1_1EMFit_html_a7cec14ec7765af815fe30e3899c6812c"><div class="ttname"><a href="classmlpack_1_1gmm_1_1EMFit.html#a7cec14ec7765af815fe30e3899c6812c">mlpack::gmm::EMFit::maxIterations</a></div><div class="ttdeci">size_t maxIterations</div><div class="ttdoc">Maximum iterations of EM algorithm. </div><div class="ttdef"><b>Definition:</b> <a href="em__fit_8hpp_source.html#l00166">em_fit.hpp:166</a></div></div>
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<div class="ttc" id="classmlpack_1_1gmm_1_1EMFit_html_a7dceacbb8ad05fa9ffca11dac4a1e372"><div class="ttname"><a href="classmlpack_1_1gmm_1_1EMFit.html#a7dceacbb8ad05fa9ffca11dac4a1e372">mlpack::gmm::EMFit::constraint</a></div><div class="ttdeci">CovarianceConstraintPolicy constraint</div><div class="ttdoc">Object which applies constraints to the covariance matrix. </div><div class="ttdef"><b>Definition:</b> <a href="em__fit_8hpp_source.html#l00172">em_fit.hpp:172</a></div></div>
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<div class="ttc" id="classmlpack_1_1gmm_1_1EMFit_html_ab1d0543bde9b1a4f2431e599a4470d93"><div class="ttname"><a href="classmlpack_1_1gmm_1_1EMFit.html#ab1d0543bde9b1a4f2431e599a4470d93">mlpack::gmm::EMFit::MaxIterations</a></div><div class="ttdeci">size_t & MaxIterations()</div><div class="ttdoc">Modify the maximum number of iterations of the EM algorithm. </div><div class="ttdef"><b>Definition:</b> <a href="em__fit_8hpp_source.html#l00124">em_fit.hpp:124</a></div></div>
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<div class="ttc" id="classmlpack_1_1gmm_1_1EMFit_html_af6c593e716a094b742d2d157f52ca75e"><div class="ttname"><a href="classmlpack_1_1gmm_1_1EMFit.html#af6c593e716a094b742d2d157f52ca75e">mlpack::gmm::EMFit::MaxIterations</a></div><div class="ttdeci">size_t MaxIterations() const </div><div class="ttdoc">Get the maximum number of iterations of the EM algorithm. </div><div class="ttdef"><b>Definition:</b> <a href="em__fit_8hpp_source.html#l00122">em_fit.hpp:122</a></div></div>
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<div class="ttc" id="kmeans_8hpp_html"><div class="ttname"><a href="kmeans_8hpp.html">kmeans.hpp</a></div></div>
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<div class="ttc" id="classmlpack_1_1gmm_1_1EMFit_html_a707dba7c98fcf7cc828bdef8e6d299d1"><div class="ttname"><a href="classmlpack_1_1gmm_1_1EMFit.html#a707dba7c98fcf7cc828bdef8e6d299d1">mlpack::gmm::EMFit::Clusterer</a></div><div class="ttdeci">InitialClusteringType & Clusterer()</div><div class="ttdoc">Modify the clusterer. </div><div class="ttdef"><b>Definition:</b> <a href="em__fit_8hpp_source.html#l00114">em_fit.hpp:114</a></div></div>
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<div class="ttc" id="classmlpack_1_1gmm_1_1EMFit_html_a629f0c991f79d2baa3fb09c49ba3834f"><div class="ttname"><a href="classmlpack_1_1gmm_1_1EMFit.html#a629f0c991f79d2baa3fb09c49ba3834f">mlpack::gmm::EMFit::EMFit</a></div><div class="ttdeci">EMFit(const size_t maxIterations=300, const double tolerance=1e-10, InitialClusteringType clusterer=InitialClusteringType(), CovarianceConstraintPolicy constraint=CovarianceConstraintPolicy())</div><div class="ttdoc">Construct the EMFit object, optionally passing an InitialClusteringType object (just in case it needs...</div></div>
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<div class="ttc" id="classmlpack_1_1gmm_1_1EMFit_html_abd646e32dea239c90f312fe0f29b0abf"><div class="ttname"><a href="classmlpack_1_1gmm_1_1EMFit.html#abd646e32dea239c90f312fe0f29b0abf">mlpack::gmm::EMFit::Constraint</a></div><div class="ttdeci">CovarianceConstraintPolicy & Constraint()</div><div class="ttdoc">Modify the covariance constraint policy class. </div><div class="ttdef"><b>Definition:</b> <a href="em__fit_8hpp_source.html#l00119">em_fit.hpp:119</a></div></div>
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<div class="ttc" id="classmlpack_1_1gmm_1_1EMFit_html_aa3aad8721a7e8538ea9c3cdacc35a996"><div class="ttname"><a href="classmlpack_1_1gmm_1_1EMFit.html#aa3aad8721a7e8538ea9c3cdacc35a996">mlpack::gmm::EMFit::Tolerance</a></div><div class="ttdeci">double Tolerance() const </div><div class="ttdoc">Get the tolerance for the convergence of the EM algorithm. </div><div class="ttdef"><b>Definition:</b> <a href="em__fit_8hpp_source.html#l00127">em_fit.hpp:127</a></div></div>
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<div class="ttc" id="classmlpack_1_1gmm_1_1EMFit_html_a9552740fd3dd1625320b402e5773b17d"><div class="ttname"><a href="classmlpack_1_1gmm_1_1EMFit.html#a9552740fd3dd1625320b402e5773b17d">mlpack::gmm::EMFit::Clusterer</a></div><div class="ttdeci">const InitialClusteringType & Clusterer() const </div><div class="ttdoc">Get the clusterer. </div><div class="ttdef"><b>Definition:</b> <a href="em__fit_8hpp_source.html#l00112">em_fit.hpp:112</a></div></div>
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<div class="ttc" id="classmlpack_1_1gmm_1_1EMFit_html_ae2c22954de90170cb1f96e36d35fcf5e"><div class="ttname"><a href="classmlpack_1_1gmm_1_1EMFit.html#ae2c22954de90170cb1f96e36d35fcf5e">mlpack::gmm::EMFit::clusterer</a></div><div class="ttdeci">InitialClusteringType clusterer</div><div class="ttdoc">Object which will perform the clustering. </div><div class="ttdef"><b>Definition:</b> <a href="em__fit_8hpp_source.html#l00170">em_fit.hpp:170</a></div></div>
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<div class="ttc" id="classmlpack_1_1gmm_1_1EMFit_html_aa068530ec69e3fc9b329f68adb6f6716"><div class="ttname"><a href="classmlpack_1_1gmm_1_1EMFit.html#aa068530ec69e3fc9b329f68adb6f6716">mlpack::gmm::EMFit::tolerance</a></div><div class="ttdeci">double tolerance</div><div class="ttdoc">Tolerance for convergence of EM. </div><div class="ttdef"><b>Definition:</b> <a href="em__fit_8hpp_source.html#l00168">em_fit.hpp:168</a></div></div>
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<div class="ttc" id="classmlpack_1_1gmm_1_1EMFit_html_a86bf5dcce8f31358af461ad78f055b37"><div class="ttname"><a href="classmlpack_1_1gmm_1_1EMFit.html#a86bf5dcce8f31358af461ad78f055b37">mlpack::gmm::EMFit::Serialize</a></div><div class="ttdeci">void Serialize(Archive &ar, const unsigned int version)</div><div class="ttdoc">Serialize the fitter. </div></div>
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