Cross Reference: /frameworks/ml/bordeaux/learning/stochastic_linear_ranker/jni/jni_stochastic_linear

Lines Matching defs:classifier
77   StochasticLinearRanker<string>* classifier = (StochasticLinearRanker<string>*) paPtr;
78   if (classifier && key_array_model && value_array_model && normalizer_model) {
87       classifier->LoadWeights(model);
102   StochasticLinearRanker<string>* classifier = (StochasticLinearRanker<string>*) paPtr;
109     classifier->SetIterationNumber((uint64) v);
114     classifier->SetNormConstraint((double) v);
119       classifier->SetRegularizationType(learning_stochastic_linear::L0);
121       classifier->SetRegularizationType(learning_stochastic_linear::L1);
123       classifier->SetRegularizationType(learning_stochastic_linear::L2);
125       classifier->SetRegularizationType(learning_stochastic_linear::L1L2);
127       classifier->SetRegularizationType(learning_stochastic_linear::L1LInf);
136     classifier->SetLambda((double) v);
141       classifier->SetUpdateType(learning_stochastic_linear::FULL_CS);
143       classifier->SetUpdateType(learning_stochastic_linear::CLIP_CS);
145       classifier->SetUpdateType(learning_stochastic_linear::REG_CS);
147       classifier->SetUpdateType(learning_stochastic_linear::SL);
149       classifier->SetUpdateType(learning_stochastic_linear::ADAPTIVE_REG);
158       classifier->SetAdaptationMode(learning_stochastic_linear::CONST);
160       classifier->SetAdaptationMode(learning_stochastic_linear::INV_LINEAR);
162       classifier->SetAdaptationMode(learning_stochastic_linear::INV_QUADRATIC);
164       classifier->SetAdaptationMode(learning_stochastic_linear::INV_SQRT);
173       classifier->SetKernelType(learning_stochastic_linear::LINEAR);
175       classifier->SetKernelType(learning_stochastic_linear::POLY);
177       classifier->SetKernelType(learning_stochastic_linear::RBF);
186     classifier->SetKernelParam((double) v);
191     classifier->SetKernelGain((double) v);
196     classifier->SetKernelBias((double) v);
201       classifier->SetRankLossType(learning_stochastic_linear::PAIRWISE);
203       classifier->SetRankLossType(learning_stochastic_linear::RECIPROCAL_RANK);
212     classifier->SetAcceptanceProbability((double) v);
217     classifier->SetMiniBatchSize((uint64) v);
222     classifier->SetGradientL0Norm((int32) v);
234   StochasticLinearRanker<string>* classifier = (StochasticLinearRanker<string>*) paPtr;
236   classifier->SaveWeights(&M_weights);
257   StochasticLinearRanker<string>* classifier = (StochasticLinearRanker<string>*) paPtr;
258   s = ConvertFloat2String((float) classifier->GetIterationNumber());
261   s = ConvertFloat2String((float) classifier->GetNormContraint());
264   float value = (float) classifier->GetRegularizationType();
284   s = ConvertFloat2String((float) classifier->GetLambda());
287   value = (float) classifier->GetUpdateType();
307   value = (float) classifier->GetAdaptationMode();
324   value = (float) classifier->GetKernelType();
338   s = ConvertFloat2String((float) classifier->GetKernelParam());
341   s = ConvertFloat2String((float) classifier->GetKernelGain());
344   s = ConvertFloat2String((float)classifier->GetKernelBias());
347   value = (float) classifier->GetRankLossType();
358   s = ConvertFloat2String((float) classifier->GetAcceptanceProbability());
361   s = ConvertFloat2String((float) classifier->GetMiniBatchSize());
364   s = ConvertFloat2String((float) classifier->GetGradientL0Norm());
376   StochasticLinearRanker<string>* classifier = (StochasticLinearRanker<string>*) paPtr;
378   classifier->SaveWeights(&M_weights);
389   StochasticLinearRanker<string>* classifier = new StochasticLinearRanker<string>();
390   return ((jlong) classifier);
397   StochasticLinearRanker<string>* classifier = (StochasticLinearRanker<string>*) paPtr;
398   delete classifier;
410   StochasticLinearRanker<string>* classifier = (StochasticLinearRanker<string>*) paPtr;
412   if (classifier && key_array_positive && value_array_positive &&
429       classifier->UpdateClassifier(sample_pos, sample_neg);
448   StochasticLinearRanker<string>* classifier = (StochasticLinearRanker<string>*) paPtr;
450   if (classifier && key_array && value_array) {
460       return classifier->ScoreSample(sample);