370 lines
9.7 KiB
Groff
370 lines
9.7 KiB
Groff
.TH "bayesnet::Boost" 3 "Version 1.0.5" "BayesNet" \" -*- nroff -*-
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.ad l
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.nh
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.SH NAME
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bayesnet::Boost
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.SH SYNOPSIS
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.br
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.PP
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.PP
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Inherits \fBbayesnet::Ensemble\fP\&.
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.PP
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Inherited by \fBbayesnet::BoostA2DE\fP, and \fBbayesnet::BoostAODE\fP\&.
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.SS "Public Member Functions"
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.in +1c
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.ti -1c
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.RI "\fBBoost\fP (bool predict_voting=false)"
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.br
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.ti -1c
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.RI "void \fBsetHyperparameters\fP (const nlohmann::json &hyperparameters_) override"
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.br
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.in -1c
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Public Member Functions inherited from \fBbayesnet::Ensemble\fP
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.in +1c
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.ti -1c
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.RI "\fBEnsemble\fP (bool predict_voting=true)"
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.br
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.ti -1c
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.RI "torch::Tensor \fBpredict\fP (torch::Tensor &X) override"
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.br
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.ti -1c
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.RI "std::vector< int > \fBpredict\fP (std::vector< std::vector< int > > &X) override"
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.br
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.ti -1c
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.RI "torch::Tensor \fBpredict_proba\fP (torch::Tensor &X) override"
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.br
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.ti -1c
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.RI "std::vector< std::vector< double > > \fBpredict_proba\fP (std::vector< std::vector< int > > &X) override"
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.br
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.ti -1c
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.RI "float \fBscore\fP (torch::Tensor &X, torch::Tensor &y) override"
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.br
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.ti -1c
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.RI "float \fBscore\fP (std::vector< std::vector< int > > &X, std::vector< int > &y) override"
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.br
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.ti -1c
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.RI "int \fBgetNumberOfNodes\fP () const override"
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.br
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.ti -1c
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.RI "int \fBgetNumberOfEdges\fP () const override"
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.br
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.ti -1c
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.RI "int \fBgetNumberOfStates\fP () const override"
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.br
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.ti -1c
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.RI "std::vector< std::string > \fBshow\fP () const override"
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.br
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.ti -1c
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.RI "std::vector< std::string > \fBgraph\fP (const std::string &title) const override"
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.br
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.ti -1c
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.RI "std::vector< std::string > \fBtopological_order\fP () override"
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.br
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.ti -1c
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.RI "std::string \fBdump_cpt\fP () const override"
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.br
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.in -1c
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Public Member Functions inherited from \fBbayesnet::Classifier\fP
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.in +1c
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.ti -1c
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.RI "\fBClassifier\fP (\fBNetwork\fP model)"
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.br
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.ti -1c
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.RI "\fBClassifier\fP & \fBfit\fP (std::vector< std::vector< int > > &X, std::vector< int > &y, const std::vector< std::string > &features, const std::string &className, std::map< std::string, std::vector< int > > &states) override"
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.br
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.ti -1c
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.RI "\fBClassifier\fP & \fBfit\fP (torch::Tensor &X, torch::Tensor &y, const std::vector< std::string > &features, const std::string &className, std::map< std::string, std::vector< int > > &states) override"
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.br
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.ti -1c
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.RI "\fBClassifier\fP & \fBfit\fP (torch::Tensor &dataset, const std::vector< std::string > &features, const std::string &className, std::map< std::string, std::vector< int > > &states) override"
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.br
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.ti -1c
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.RI "\fBClassifier\fP & \fBfit\fP (torch::Tensor &dataset, const std::vector< std::string > &features, const std::string &className, std::map< std::string, std::vector< int > > &states, const torch::Tensor &weights) override"
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.br
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.ti -1c
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.RI "void \fBaddNodes\fP ()"
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.br
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.ti -1c
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.RI "int \fBgetClassNumStates\fP () const override"
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.br
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.ti -1c
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.RI "status_t \fBgetStatus\fP () const override"
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.br
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.ti -1c
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.RI "std::string \fBgetVersion\fP () override"
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.br
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.ti -1c
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.RI "std::vector< std::string > \fBgetNotes\fP () const override"
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.br
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.ti -1c
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.RI "void \fBsetHyperparameters\fP (const nlohmann::json &hyperparameters) override"
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.br
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.in -1c
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Public Member Functions inherited from \fBbayesnet::BaseClassifier\fP
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.in +1c
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.ti -1c
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.RI "std::vector< std::string > & \fBgetValidHyperparameters\fP ()"
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.br
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.in -1c
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.SS "Protected Member Functions"
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.in +1c
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.ti -1c
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.RI "std::vector< int > \fBfeatureSelection\fP (torch::Tensor &weights_)"
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.br
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.ti -1c
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.RI "void \fBbuildModel\fP (const torch::Tensor &weights) override"
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.br
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.ti -1c
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.RI "std::tuple< torch::Tensor &, double, bool > \fBupdate_weights\fP (torch::Tensor &ytrain, torch::Tensor &ypred, torch::Tensor &weights)"
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.br
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.ti -1c
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.RI "std::tuple< torch::Tensor &, double, bool > \fBupdate_weights_block\fP (int k, torch::Tensor &ytrain, torch::Tensor &weights)"
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.br
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.in -1c
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Protected Member Functions inherited from \fBbayesnet::Ensemble\fP
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.in +1c
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.ti -1c
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.RI "torch::Tensor \fBpredict_average_voting\fP (torch::Tensor &X)"
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.br
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.ti -1c
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.RI "std::vector< std::vector< double > > \fBpredict_average_voting\fP (std::vector< std::vector< int > > &X)"
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.br
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.ti -1c
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.RI "torch::Tensor \fBpredict_average_proba\fP (torch::Tensor &X)"
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.br
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.ti -1c
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.RI "std::vector< std::vector< double > > \fBpredict_average_proba\fP (std::vector< std::vector< int > > &X)"
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.br
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.ti -1c
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.RI "torch::Tensor \fBcompute_arg_max\fP (torch::Tensor &X)"
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.br
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.ti -1c
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.RI "std::vector< int > \fBcompute_arg_max\fP (std::vector< std::vector< double > > &X)"
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.br
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.ti -1c
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.RI "torch::Tensor \fBvoting\fP (torch::Tensor &votes)"
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.br
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.ti -1c
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.RI "void \fBtrainModel\fP (const torch::Tensor &weights) override"
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.br
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.in -1c
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Protected Member Functions inherited from \fBbayesnet::Classifier\fP
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.in +1c
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.ti -1c
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.RI "void \fBcheckFitParameters\fP ()"
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.br
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.ti -1c
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.RI "void \fBbuildDataset\fP (torch::Tensor &y)"
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.br
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.in -1c
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.SS "Protected Attributes"
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.in +1c
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.ti -1c
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.RI "torch::Tensor \fBX_train\fP"
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.br
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.ti -1c
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.RI "torch::Tensor \fBy_train\fP"
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.br
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.ti -1c
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.RI "torch::Tensor \fBX_test\fP"
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.br
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.ti -1c
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.RI "torch::Tensor \fBy_test\fP"
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.br
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.ti -1c
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.RI "bool \fBbisection\fP = true"
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.br
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.ti -1c
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.RI "int \fBmaxTolerance\fP = 3"
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.br
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.ti -1c
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.RI "std::string \fBorder_algorithm\fP"
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.br
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.ti -1c
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.RI "bool \fBconvergence\fP = true"
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.br
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.ti -1c
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.RI "bool \fBconvergence_best\fP = false"
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.br
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.ti -1c
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.RI "bool \fBselectFeatures\fP = false"
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.br
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.ti -1c
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.RI "std::string \fBselect_features_algorithm\fP = Orders\&.DESC"
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.br
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.ti -1c
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.RI "FeatureSelect * \fBfeatureSelector\fP = nullptr"
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.br
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.ti -1c
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.RI "double \fBthreshold\fP = \-1"
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.br
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.ti -1c
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.RI "bool \fBblock_update\fP = false"
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.br
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.in -1c
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Protected Attributes inherited from \fBbayesnet::Ensemble\fP
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.in +1c
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.ti -1c
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.RI "unsigned \fBn_models\fP"
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.br
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.ti -1c
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.RI "std::vector< std::unique_ptr< \fBClassifier\fP > > \fBmodels\fP"
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.br
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.ti -1c
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.RI "std::vector< double > \fBsignificanceModels\fP"
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.br
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.ti -1c
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.RI "bool \fBpredict_voting\fP"
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.br
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.in -1c
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Protected Attributes inherited from \fBbayesnet::Classifier\fP
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.in +1c
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.ti -1c
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.RI "bool \fBfitted\fP"
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.br
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.ti -1c
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.RI "unsigned int \fBm\fP"
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.br
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.ti -1c
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.RI "unsigned int \fBn\fP"
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.br
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.ti -1c
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.RI "\fBNetwork\fP \fBmodel\fP"
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.br
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.ti -1c
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.RI "Metrics \fBmetrics\fP"
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.br
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.ti -1c
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.RI "std::vector< std::string > \fBfeatures\fP"
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.br
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.ti -1c
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.RI "std::string \fBclassName\fP"
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.br
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.ti -1c
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.RI "std::map< std::string, std::vector< int > > \fBstates\fP"
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.br
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.ti -1c
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.RI "torch::Tensor \fBdataset\fP"
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.br
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.ti -1c
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.RI "status_t \fBstatus\fP = NORMAL"
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.br
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.ti -1c
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.RI "std::vector< std::string > \fBnotes\fP"
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.br
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.in -1c
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Protected Attributes inherited from \fBbayesnet::BaseClassifier\fP
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.in +1c
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.ti -1c
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.RI "std::vector< std::string > \fBvalidHyperparameters\fP"
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.br
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.in -1c
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.SH "Detailed Description"
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.PP
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Definition at line \fB27\fP of file \fBBoost\&.h\fP\&.
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.SH "Constructor & Destructor Documentation"
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.PP
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.SS "bayesnet::Boost::Boost (bool predict_voting = \fRfalse\fP)\fR [explicit]\fP"
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.PP
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Definition at line \fB13\fP of file \fBBoost\&.cc\fP\&.
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.SH "Member Function Documentation"
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.PP
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.SS "void bayesnet::Boost::buildModel (const torch::Tensor & weights)\fR [override]\fP, \fR [protected]\fP, \fR [virtual]\fP"
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.PP
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Implements \fBbayesnet::Classifier\fP\&.
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.PP
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Definition at line \fB71\fP of file \fBBoost\&.cc\fP\&.
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.SS "std::vector< int > bayesnet::Boost::featureSelection (torch::Tensor & weights_)\fR [protected]\fP"
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.PP
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Definition at line \fB102\fP of file \fBBoost\&.cc\fP\&.
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.SS "void bayesnet::Boost::setHyperparameters (const nlohmann::json & hyperparameters_)\fR [override]\fP, \fR [virtual]\fP"
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.PP
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Implements \fBbayesnet::BaseClassifier\fP\&.
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.PP
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Definition at line \fB18\fP of file \fBBoost\&.cc\fP\&.
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.SS "std::tuple< torch::Tensor &, double, bool > bayesnet::Boost::update_weights (torch::Tensor & ytrain, torch::Tensor & ypred, torch::Tensor & weights)\fR [protected]\fP"
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.PP
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Definition at line \fB123\fP of file \fBBoost\&.cc\fP\&.
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.SS "std::tuple< torch::Tensor &, double, bool > bayesnet::Boost::update_weights_block (int k, torch::Tensor & ytrain, torch::Tensor & weights)\fR [protected]\fP"
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.PP
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Definition at line \fB150\fP of file \fBBoost\&.cc\fP\&.
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.SH "Member Data Documentation"
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.PP
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.SS "bool bayesnet::Boost::bisection = true\fR [protected]\fP"
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.PP
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Definition at line \fB39\fP of file \fBBoost\&.h\fP\&.
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.SS "bool bayesnet::Boost::block_update = false\fR [protected]\fP"
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.PP
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Definition at line \fB48\fP of file \fBBoost\&.h\fP\&.
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.SS "bool bayesnet::Boost::convergence = true\fR [protected]\fP"
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.PP
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Definition at line \fB42\fP of file \fBBoost\&.h\fP\&.
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.SS "bool bayesnet::Boost::convergence_best = false\fR [protected]\fP"
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.PP
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Definition at line \fB43\fP of file \fBBoost\&.h\fP\&.
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.SS "FeatureSelect* bayesnet::Boost::featureSelector = nullptr\fR [protected]\fP"
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.PP
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Definition at line \fB46\fP of file \fBBoost\&.h\fP\&.
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.SS "int bayesnet::Boost::maxTolerance = 3\fR [protected]\fP"
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.PP
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Definition at line \fB40\fP of file \fBBoost\&.h\fP\&.
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.SS "std::string bayesnet::Boost::order_algorithm\fR [protected]\fP"
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.PP
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Definition at line \fB41\fP of file \fBBoost\&.h\fP\&.
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.SS "std::string bayesnet::Boost::select_features_algorithm = Orders\&.DESC\fR [protected]\fP"
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.PP
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Definition at line \fB45\fP of file \fBBoost\&.h\fP\&.
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.SS "bool bayesnet::Boost::selectFeatures = false\fR [protected]\fP"
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.PP
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Definition at line \fB44\fP of file \fBBoost\&.h\fP\&.
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.SS "double bayesnet::Boost::threshold = \-1\fR [protected]\fP"
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.PP
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Definition at line \fB47\fP of file \fBBoost\&.h\fP\&.
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.SS "torch::Tensor bayesnet::Boost::X_test\fR [protected]\fP"
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.PP
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Definition at line \fB37\fP of file \fBBoost\&.h\fP\&.
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.SS "torch::Tensor bayesnet::Boost::X_train\fR [protected]\fP"
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.PP
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Definition at line \fB37\fP of file \fBBoost\&.h\fP\&.
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.SS "torch::Tensor bayesnet::Boost::y_test\fR [protected]\fP"
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.PP
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Definition at line \fB37\fP of file \fBBoost\&.h\fP\&.
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.SS "torch::Tensor bayesnet::Boost::y_train\fR [protected]\fP"
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.PP
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Definition at line \fB37\fP of file \fBBoost\&.h\fP\&.
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.SH "Author"
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.PP
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Generated automatically by Doxygen for BayesNet from the source code\&.
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