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838 lines
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<li class="navelem"><a class="el" href="namespacemlpack.html">mlpack</a></li><li class="navelem"><a class="el" href="namespacemlpack_1_1regression.html">regression</a></li><li class="navelem"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html">SoftmaxRegressionFunction</a></li> </ul>
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<a href="#pub-methods">Public Member Functions</a> |
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<div class="title">mlpack::regression::SoftmaxRegressionFunction Class Reference</div> </div>
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<table class="memberdecls">
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
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Public Member Functions</h2></td></tr>
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<tr class="memitem:a04fb165933a254fa25c59a2c7abb93cd"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#a04fb165933a254fa25c59a2c7abb93cd">SoftmaxRegressionFunction</a> (const arma::mat &<a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#a2e3f74b4fcf2b741173be496b6529714">data</a>, const arma::Row< size_t > &labels, const size_t <a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#a101ba2df474ecdc8df13a578894812a6">numClasses</a>, const double <a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#a670dad5b9bcd03bf0af094a1a4ef3d7f">lambda</a>=0.0001, const bool <a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#aa1347374266670a5662bde98c7554b9f">fitIntercept</a>=false)</td></tr>
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<tr class="memdesc:a04fb165933a254fa25c59a2c7abb93cd"><td class="mdescLeft"> </td><td class="mdescRight">Construct the Softmax Regression objective function with the given parameters. <a href="#a04fb165933a254fa25c59a2c7abb93cd">More...</a><br /></td></tr>
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<tr class="separator:a04fb165933a254fa25c59a2c7abb93cd"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a9a019e8fc0180563709261da7a2873ce"><td class="memItemLeft" align="right" valign="top">double </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#a9a019e8fc0180563709261da7a2873ce">Evaluate</a> (const arma::mat &parameters) const </td></tr>
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<tr class="memdesc:a9a019e8fc0180563709261da7a2873ce"><td class="mdescLeft"> </td><td class="mdescRight">Evaluates the objective function of the softmax regression model using the given parameters. <a href="#a9a019e8fc0180563709261da7a2873ce">More...</a><br /></td></tr>
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<tr class="separator:a9a019e8fc0180563709261da7a2873ce"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:af33aac8a050be127b82f40ff60cf7981"><td class="memItemLeft" align="right" valign="top">size_t </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#af33aac8a050be127b82f40ff60cf7981">FeatureSize</a> () const </td></tr>
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<tr class="memdesc:af33aac8a050be127b82f40ff60cf7981"><td class="mdescLeft"> </td><td class="mdescRight">Gets the features size of the training data. <a href="#af33aac8a050be127b82f40ff60cf7981">More...</a><br /></td></tr>
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<tr class="separator:af33aac8a050be127b82f40ff60cf7981"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a2b8f1ae12cb6aed7031b1c532a6fbd6f"><td class="memItemLeft" align="right" valign="top">bool </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#a2b8f1ae12cb6aed7031b1c532a6fbd6f">FitIntercept</a> () const </td></tr>
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<tr class="memdesc:a2b8f1ae12cb6aed7031b1c532a6fbd6f"><td class="mdescLeft"> </td><td class="mdescRight">Gets the intercept flag. <a href="#a2b8f1ae12cb6aed7031b1c532a6fbd6f">More...</a><br /></td></tr>
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<tr class="separator:a2b8f1ae12cb6aed7031b1c532a6fbd6f"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:aff612342ba94ce27464f9b094b27d9e9"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#aff612342ba94ce27464f9b094b27d9e9">GetGroundTruthMatrix</a> (const arma::Row< size_t > &labels, arma::sp_mat &<a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#a6f41ab9a1064fc773375e0aa94095120">groundTruth</a>)</td></tr>
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<tr class="memdesc:aff612342ba94ce27464f9b094b27d9e9"><td class="mdescLeft"> </td><td class="mdescRight">Constructs the ground truth label matrix with the passed labels. <a href="#aff612342ba94ce27464f9b094b27d9e9">More...</a><br /></td></tr>
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<tr class="separator:aff612342ba94ce27464f9b094b27d9e9"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:ab380449ee1fef938ff483abf91c88b2d"><td class="memItemLeft" align="right" valign="top">const arma::mat & </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#ab380449ee1fef938ff483abf91c88b2d">GetInitialPoint</a> () const </td></tr>
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<tr class="memdesc:ab380449ee1fef938ff483abf91c88b2d"><td class="mdescLeft"> </td><td class="mdescRight">Return the initial point for the optimization. <a href="#ab380449ee1fef938ff483abf91c88b2d">More...</a><br /></td></tr>
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<tr class="separator:ab380449ee1fef938ff483abf91c88b2d"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a8e5db78a1d8bdcd2fd34bba2a119a6ec"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#a8e5db78a1d8bdcd2fd34bba2a119a6ec">GetProbabilitiesMatrix</a> (const arma::mat &parameters, arma::mat &probabilities) const </td></tr>
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<tr class="memdesc:a8e5db78a1d8bdcd2fd34bba2a119a6ec"><td class="mdescLeft"> </td><td class="mdescRight">Evaluate the probabilities matrix with the passed parameters. <a href="#a8e5db78a1d8bdcd2fd34bba2a119a6ec">More...</a><br /></td></tr>
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<tr class="separator:a8e5db78a1d8bdcd2fd34bba2a119a6ec"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a6dbfb5cd32ab9e770fb965dc778adde4"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#a6dbfb5cd32ab9e770fb965dc778adde4">Gradient</a> (const arma::mat &parameters, arma::mat &gradient) const </td></tr>
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<tr class="memdesc:a6dbfb5cd32ab9e770fb965dc778adde4"><td class="mdescLeft"> </td><td class="mdescRight">Evaluates the gradient values of the objective function given the current set of parameters. <a href="#a6dbfb5cd32ab9e770fb965dc778adde4">More...</a><br /></td></tr>
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<tr class="separator:a6dbfb5cd32ab9e770fb965dc778adde4"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:aef36a1980d482c89e57e5a39c36e0758"><td class="memItemLeft" align="right" valign="top">const arma::mat </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#aef36a1980d482c89e57e5a39c36e0758">InitializeWeights</a> ()</td></tr>
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<tr class="memdesc:aef36a1980d482c89e57e5a39c36e0758"><td class="mdescLeft"> </td><td class="mdescRight">Initializes the parameters of the model to suitable values. <a href="#aef36a1980d482c89e57e5a39c36e0758">More...</a><br /></td></tr>
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<tr class="separator:aef36a1980d482c89e57e5a39c36e0758"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:ab4406833a9268b8729d53e7ff3a46d21"><td class="memItemLeft" align="right" valign="top">double & </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#ab4406833a9268b8729d53e7ff3a46d21">Lambda</a> ()</td></tr>
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<tr class="memdesc:ab4406833a9268b8729d53e7ff3a46d21"><td class="mdescLeft"> </td><td class="mdescRight">Sets the regularization parameter. <a href="#ab4406833a9268b8729d53e7ff3a46d21">More...</a><br /></td></tr>
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<tr class="separator:ab4406833a9268b8729d53e7ff3a46d21"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:aa9e4a31b2e3df431f3d4fa78cbbc1d67"><td class="memItemLeft" align="right" valign="top">double </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#aa9e4a31b2e3df431f3d4fa78cbbc1d67">Lambda</a> () const </td></tr>
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<tr class="memdesc:aa9e4a31b2e3df431f3d4fa78cbbc1d67"><td class="mdescLeft"> </td><td class="mdescRight">Gets the regularization parameter. <a href="#aa9e4a31b2e3df431f3d4fa78cbbc1d67">More...</a><br /></td></tr>
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<tr class="separator:aa9e4a31b2e3df431f3d4fa78cbbc1d67"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a8103ebfe7f88389b2345e80375947f8b"><td class="memItemLeft" align="right" valign="top">size_t </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#a8103ebfe7f88389b2345e80375947f8b">NumClasses</a> () const </td></tr>
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<tr class="memdesc:a8103ebfe7f88389b2345e80375947f8b"><td class="mdescLeft"> </td><td class="mdescRight">Gets the number of classes. <a href="#a8103ebfe7f88389b2345e80375947f8b">More...</a><br /></td></tr>
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<tr class="separator:a8103ebfe7f88389b2345e80375947f8b"><td class="memSeparator" colspan="2"> </td></tr>
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</table><table class="memberdecls">
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-static-methods"></a>
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Static Public Member Functions</h2></td></tr>
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<tr class="memitem:a9d6309e92e85eb0d027cf3f4b4fabb80"><td class="memItemLeft" align="right" valign="top">static const arma::mat </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#a9d6309e92e85eb0d027cf3f4b4fabb80">InitializeWeights</a> (const size_t featureSize, const size_t <a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#a101ba2df474ecdc8df13a578894812a6">numClasses</a>, const bool <a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#aa1347374266670a5662bde98c7554b9f">fitIntercept</a>=false)</td></tr>
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<tr class="memdesc:a9d6309e92e85eb0d027cf3f4b4fabb80"><td class="mdescLeft"> </td><td class="mdescRight">Initialize Softmax Regression weights (trainable parameters) with the given parameters. <a href="#a9d6309e92e85eb0d027cf3f4b4fabb80">More...</a><br /></td></tr>
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<tr class="separator:a9d6309e92e85eb0d027cf3f4b4fabb80"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a172e40489a847002a43abe1e4351f58a"><td class="memItemLeft" align="right" valign="top">static void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#a172e40489a847002a43abe1e4351f58a">InitializeWeights</a> (arma::mat &weights, const size_t featureSize, const size_t <a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#a101ba2df474ecdc8df13a578894812a6">numClasses</a>, const bool <a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#aa1347374266670a5662bde98c7554b9f">fitIntercept</a>=false)</td></tr>
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<tr class="memdesc:a172e40489a847002a43abe1e4351f58a"><td class="mdescLeft"> </td><td class="mdescRight">Initialize Softmax Regression weights (trainable parameters) with the given parameters. <a href="#a172e40489a847002a43abe1e4351f58a">More...</a><br /></td></tr>
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<tr class="separator:a172e40489a847002a43abe1e4351f58a"><td class="memSeparator" colspan="2"> </td></tr>
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</table><table class="memberdecls">
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pri-attribs"></a>
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Private Attributes</h2></td></tr>
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<tr class="memitem:a2e3f74b4fcf2b741173be496b6529714"><td class="memItemLeft" align="right" valign="top">const arma::mat & </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#a2e3f74b4fcf2b741173be496b6529714">data</a></td></tr>
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<tr class="memdesc:a2e3f74b4fcf2b741173be496b6529714"><td class="mdescLeft"> </td><td class="mdescRight">Training data matrix. <a href="#a2e3f74b4fcf2b741173be496b6529714">More...</a><br /></td></tr>
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<tr class="separator:a2e3f74b4fcf2b741173be496b6529714"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:aa1347374266670a5662bde98c7554b9f"><td class="memItemLeft" align="right" valign="top">bool </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#aa1347374266670a5662bde98c7554b9f">fitIntercept</a></td></tr>
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<tr class="memdesc:aa1347374266670a5662bde98c7554b9f"><td class="mdescLeft"> </td><td class="mdescRight">Intercept term flag. <a href="#aa1347374266670a5662bde98c7554b9f">More...</a><br /></td></tr>
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<tr class="separator:aa1347374266670a5662bde98c7554b9f"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a6f41ab9a1064fc773375e0aa94095120"><td class="memItemLeft" align="right" valign="top">arma::sp_mat </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#a6f41ab9a1064fc773375e0aa94095120">groundTruth</a></td></tr>
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<tr class="memdesc:a6f41ab9a1064fc773375e0aa94095120"><td class="mdescLeft"> </td><td class="mdescRight">Label matrix for the provided data. <a href="#a6f41ab9a1064fc773375e0aa94095120">More...</a><br /></td></tr>
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<tr class="memitem:acb264cabc7ece311ce0a4fc716ac06a0"><td class="memItemLeft" align="right" valign="top">arma::mat </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#acb264cabc7ece311ce0a4fc716ac06a0">initialPoint</a></td></tr>
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<tr class="memdesc:acb264cabc7ece311ce0a4fc716ac06a0"><td class="mdescLeft"> </td><td class="mdescRight">Initial parameter point. <a href="#acb264cabc7ece311ce0a4fc716ac06a0">More...</a><br /></td></tr>
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<tr class="separator:acb264cabc7ece311ce0a4fc716ac06a0"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:a670dad5b9bcd03bf0af094a1a4ef3d7f"><td class="memItemLeft" align="right" valign="top">double </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#a670dad5b9bcd03bf0af094a1a4ef3d7f">lambda</a></td></tr>
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<tr class="memdesc:a670dad5b9bcd03bf0af094a1a4ef3d7f"><td class="mdescLeft"> </td><td class="mdescRight">L2-regularization constant. <a href="#a670dad5b9bcd03bf0af094a1a4ef3d7f">More...</a><br /></td></tr>
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<tr class="memitem:a101ba2df474ecdc8df13a578894812a6"><td class="memItemLeft" align="right" valign="top">size_t </td><td class="memItemRight" valign="bottom"><a class="el" href="classmlpack_1_1regression_1_1SoftmaxRegressionFunction.html#a101ba2df474ecdc8df13a578894812a6">numClasses</a></td></tr>
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<tr class="memdesc:a101ba2df474ecdc8df13a578894812a6"><td class="mdescLeft"> </td><td class="mdescRight">Number of classes. <a href="#a101ba2df474ecdc8df13a578894812a6">More...</a><br /></td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
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<div class="textblock">
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<p>Definition at line <a class="el" href="softmax__regression__function_8hpp_source.html#l00021">21</a> of file <a class="el" href="softmax__regression__function_8hpp_source.html">softmax_regression_function.hpp</a>.</p>
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</div><h2 class="groupheader">Constructor & Destructor Documentation</h2>
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<td class="memname">mlpack::regression::SoftmaxRegressionFunction::SoftmaxRegressionFunction </td>
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<td class="paramtype">const arma::mat & </td>
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<p>Construct the Softmax Regression objective function with the given parameters. </p>
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<dl class="params"><dt>Parameters</dt><dd>
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<table class="params">
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<tr><td class="paramname">data</td><td>Input training data, each column associate with one sample </td></tr>
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<tr><td class="paramname">labels</td><td>Labels associated with the feature data. </td></tr>
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<tr><td class="paramname">inputSize</td><td>Size of the input feature vector. </td></tr>
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<tr><td class="paramname">numClasses</td><td>Number of classes for classification. </td></tr>
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<tr><td class="paramname">lambda</td><td>L2-regularization constant. </td></tr>
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<h2 class="groupheader">Member Function Documentation</h2>
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<td class="memname">double mlpack::regression::SoftmaxRegressionFunction::Evaluate </td>
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<td>(</td>
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<p>Evaluates the objective function of the softmax regression model using the given parameters. </p>
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<p>The cost function has terms for the log likelihood error and the regularization cost. The objective function takes a low value when the model generalizes well for the given training data, while having small parameter values.</p>
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<dl class="params"><dt>Parameters</dt><dd>
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<td class="memname">size_t mlpack::regression::SoftmaxRegressionFunction::FeatureSize </td>
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<td>(</td>
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<p>Gets the features size of the training data. </p>
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<p>Definition at line <a class="el" href="softmax__regression__function_8hpp_source.html#l00121">121</a> of file <a class="el" href="softmax__regression__function_8hpp_source.html">softmax_regression_function.hpp</a>.</p>
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<p>References <a class="el" href="softmax__regression__function_8hpp_source.html#l00147">fitIntercept</a>, and <a class="el" href="softmax__regression__function_8hpp_source.html#l00141">initialPoint</a>.</p>
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<td class="memname">bool mlpack::regression::SoftmaxRegressionFunction::FitIntercept </td>
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<p>Gets the intercept flag. </p>
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<p>Definition at line <a class="el" href="softmax__regression__function_8hpp_source.html#l00133">133</a> of file <a class="el" href="softmax__regression__function_8hpp_source.html">softmax_regression_function.hpp</a>.</p>
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<p>References <a class="el" href="softmax__regression__function_8hpp_source.html#l00147">fitIntercept</a>.</p>
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<td class="memname">void mlpack::regression::SoftmaxRegressionFunction::GetGroundTruthMatrix </td>
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<td>(</td>
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<p>Constructs the ground truth label matrix with the passed labels. </p>
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<td class="memname">const arma::mat& mlpack::regression::SoftmaxRegressionFunction::GetInitialPoint </td>
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<p>Return the initial point for the optimization. </p>
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<p>Definition at line <a class="el" href="softmax__regression__function_8hpp_source.html#l00115">115</a> of file <a class="el" href="softmax__regression__function_8hpp_source.html">softmax_regression_function.hpp</a>.</p>
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<p>References <a class="el" href="softmax__regression__function_8hpp_source.html#l00141">initialPoint</a>.</p>
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<td class="memname">void mlpack::regression::SoftmaxRegressionFunction::GetProbabilitiesMatrix </td>
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<td>(</td>
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<p>Evaluate the probabilities matrix with the passed parameters. </p>
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<p>probabilities(i, j) = exp( * data_j) / sum_k(exp( * data_j)). It represents the probability of data_j belongs to class i.</p>
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<dl class="params"><dt>Parameters</dt><dd>
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<tr><td class="paramname">parameters</td><td>Current values of the model parameters. </td></tr>
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<tr><td class="paramname">probabilities</td><td>Pointer to arma::mat which stores the probabilities. </td></tr>
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<td class="memname">void mlpack::regression::SoftmaxRegressionFunction::Gradient </td>
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<td>(</td>
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<p>Evaluates the gradient values of the objective function given the current set of parameters. </p>
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<p>The function calculates the probabilities for each class given the parameters, and computes the gradients based on the difference from the ground truth.</p>
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<dl class="params"><dt>Parameters</dt><dd>
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<tr><td class="paramname">parameters</td><td>Current values of the model parameters. </td></tr>
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<tr><td class="paramname">gradient</td><td>Matrix where gradient values will be stored. </td></tr>
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<p>Initializes the parameters of the model to suitable values. </p>
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<p>Initialize Softmax Regression weights (trainable parameters) with the given parameters. </p>
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<dl class="section return"><dt>Returns</dt><dd>Initialized model weights. </dd></dl>
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<p>Initialize Softmax Regression weights (trainable parameters) with the given parameters. </p>
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<tr><td class="paramname">weights</td><td>This will be filled with the initialized model weights. </td></tr>
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<tr><td class="paramname">numClasses</td><td>Number of classes for classification. </td></tr>
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<p>Sets the regularization parameter. </p>
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<p>Definition at line <a class="el" href="softmax__regression__function_8hpp_source.html#l00128">128</a> of file <a class="el" href="softmax__regression__function_8hpp_source.html">softmax_regression_function.hpp</a>.</p>
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<p>References <a class="el" href="softmax__regression__function_8hpp_source.html#l00145">lambda</a>.</p>
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<td class="memname">double mlpack::regression::SoftmaxRegressionFunction::Lambda </td>
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<td>(</td>
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<p>Gets the regularization parameter. </p>
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<p>Definition at line <a class="el" href="softmax__regression__function_8hpp_source.html#l00130">130</a> of file <a class="el" href="softmax__regression__function_8hpp_source.html">softmax_regression_function.hpp</a>.</p>
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<p>References <a class="el" href="softmax__regression__function_8hpp_source.html#l00145">lambda</a>.</p>
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<td class="memname">size_t mlpack::regression::SoftmaxRegressionFunction::NumClasses </td>
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<p>Gets the number of classes. </p>
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<p>Definition at line <a class="el" href="softmax__regression__function_8hpp_source.html#l00118">118</a> of file <a class="el" href="softmax__regression__function_8hpp_source.html">softmax_regression_function.hpp</a>.</p>
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<p>References <a class="el" href="softmax__regression__function_8hpp_source.html#l00143">numClasses</a>.</p>
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<h2 class="groupheader">Member Data Documentation</h2>
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<td class="memname">const arma::mat& mlpack::regression::SoftmaxRegressionFunction::data</td>
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<p>Training data matrix. </p>
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<p>Definition at line <a class="el" href="softmax__regression__function_8hpp_source.html#l00137">137</a> of file <a class="el" href="softmax__regression__function_8hpp_source.html">softmax_regression_function.hpp</a>.</p>
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<p>Intercept term flag. </p>
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<p>Definition at line <a class="el" href="softmax__regression__function_8hpp_source.html#l00147">147</a> of file <a class="el" href="softmax__regression__function_8hpp_source.html">softmax_regression_function.hpp</a>.</p>
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<p>Referenced by <a class="el" href="softmax__regression__function_8hpp_source.html#l00121">FeatureSize()</a>, and <a class="el" href="softmax__regression__function_8hpp_source.html#l00133">FitIntercept()</a>.</p>
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<td class="memname">arma::sp_mat mlpack::regression::SoftmaxRegressionFunction::groundTruth</td>
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<p>Label matrix for the provided data. </p>
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<p>Definition at line <a class="el" href="softmax__regression__function_8hpp_source.html#l00139">139</a> of file <a class="el" href="softmax__regression__function_8hpp_source.html">softmax_regression_function.hpp</a>.</p>
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<p>Initial parameter point. </p>
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<p>Definition at line <a class="el" href="softmax__regression__function_8hpp_source.html#l00141">141</a> of file <a class="el" href="softmax__regression__function_8hpp_source.html">softmax_regression_function.hpp</a>.</p>
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<p>Referenced by <a class="el" href="softmax__regression__function_8hpp_source.html#l00121">FeatureSize()</a>, and <a class="el" href="softmax__regression__function_8hpp_source.html#l00115">GetInitialPoint()</a>.</p>
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<td class="memname">double mlpack::regression::SoftmaxRegressionFunction::lambda</td>
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<p>L2-regularization constant. </p>
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<p>Definition at line <a class="el" href="softmax__regression__function_8hpp_source.html#l00145">145</a> of file <a class="el" href="softmax__regression__function_8hpp_source.html">softmax_regression_function.hpp</a>.</p>
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<p>Referenced by <a class="el" href="softmax__regression__function_8hpp_source.html#l00128">Lambda()</a>.</p>
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<td class="memname">size_t mlpack::regression::SoftmaxRegressionFunction::numClasses</td>
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<p>Number of classes. </p>
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<p>Definition at line <a class="el" href="softmax__regression__function_8hpp_source.html#l00143">143</a> of file <a class="el" href="softmax__regression__function_8hpp_source.html">softmax_regression_function.hpp</a>.</p>
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<p>Referenced by <a class="el" href="softmax__regression__function_8hpp_source.html#l00118">NumClasses()</a>.</p>
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<hr/>The documentation for this class was generated from the following file:<ul>
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<li>src/mlpack/methods/softmax_regression/<a class="el" href="softmax__regression__function_8hpp_source.html">softmax_regression_function.hpp</a></li>
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