, including all inherited members.
| _classname_() | PLearn::NNet | [static] |
| _getOptionList_() | PLearn::NNet | [static] |
| _getRemoteMethodMap_() | PLearn::NNet | [static] |
| _isa_(const Object *o) | PLearn::NNet | [static] |
| _new_instance_for_typemap_() | PLearn::NNet | [static] |
| _static_initialize_() | PLearn::NNet | [static] |
| _static_initializer_ | PLearn::NNet | [static] |
| alpha_adaboost | PLearn::NNet | [protected] |
| applyTransferFunc(const Var &before_transfer_func, Var &output) | PLearn::NNet | [protected] |
| asString() const | PLearn::Object | [virtual] |
| asStringRemoteTransmit() const | PLearn::Object | [virtual] |
| b_costs | PLearn::PLearner | [mutable, protected] |
| b_inputs | PLearn::PLearner | [mutable, protected] |
| b_outputs | PLearn::PLearner | [mutable, protected] |
| b_targets | PLearn::PLearner | [mutable, protected] |
| b_weights | PLearn::PLearner | [mutable, protected] |
| bag_inputs | PLearn::NNet | [protected] |
| bag_size | PLearn::NNet | [protected] |
| batch_size | PLearn::NNet | |
| batchComputeOutputAndConfidence(VMat inputs, real probability, VMat outputs_and_confidence) const | PLearn::PLearner | [virtual] |
| bias_decay | PLearn::NNet | |
| build() | PLearn::NNet | [virtual] |
| build_() | PLearn::NNet | [private] |
| build_from_train_set() | PLearn::PLearner | [inline, protected, virtual] |
| buildBagOutputFromBagInputs(const Var &input, Var &before_transfer_func, const Var &bag_inputs, const Var &bag_size, Var &bag_output) | PLearn::NNet | [protected] |
| buildCosts(const Var &output, const Var &target, const Var &hidden_layer, const Var &before_transfer_func) | PLearn::NNet | [protected] |
| buildFuncs(const Var &the_input, const Var &the_output, const Var &the_target, const Var &the_sampleweight, const Var &the_bag_size) | PLearn::NNet | [protected] |
| buildOutputFromInput(const Var &the_input, Var &hidden_layer, Var &before_transfer_func) | PLearn::NNet | [protected] |
| buildPenalties(const Var &hidden_layer) | PLearn::NNet | [protected, virtual] |
| buildTargetAndWeight() | PLearn::NNet | [protected] |
| call(const string &methodname, int nargs, PStream &io) | PLearn::Object | [virtual] |
| changeOption(const string &optionname, const string &value) | PLearn::Object | |
| changeOptions(const map< string, string > &name_value) | PLearn::Object | [virtual] |
| classification_regularizer | PLearn::NNet | |
| classname() const | PLearn::NNet | [virtual] |
| computeConfidenceFromOutput(const Vec &input, const Vec &output, real probability, TVec< pair< real, real > > &intervals) const | PLearn::PLearner | [virtual] |
| computeCostsFromOutputs(const Vec &input, const Vec &output, const Vec &target, Vec &costs) const | PLearn::NNet | [virtual] |
| computeCostsOnly(const Vec &input, const Vec &target, Vec &costs) const | PLearn::PLearner | [virtual] |
| computeInputOutputConfMat(VMat inputs, real probability) const | PLearn::PLearner | |
| computeInputOutputMat(VMat inputs) const | PLearn::PLearner | |
| computeOutput(const Vec &input, Vec &output) const | PLearn::NNet | [virtual] |
| computeOutputAndCosts(const Vec &input, const Vec &target, Vec &output, Vec &costs) const | PLearn::NNet | [virtual] |
| computeOutputConfMat(VMat inputs, real probability) const | PLearn::PLearner | |
| computeOutputCovMat(const Mat &inputs, Mat &outputs, TVec< Mat > &covariance_matrices) const | PLearn::PLearner | [virtual] |
| computeOutputs(const Mat &input, Mat &output) const | PLearn::PLearner | [virtual] |
| computeOutputsAndCosts(const Mat &input, const Mat &target, Mat &output, Mat &costs) const | PLearn::PLearner | [virtual] |
| cost_funcs | PLearn::NNet | |
| costs | PLearn::NNet | [protected] |
| declareMethods(RemoteMethodMap &rmm) | PLearn::PLearner | [protected, static] |
| declareOptions(OptionList &ol) | PLearn::NNet | [protected, static] |
| declaringFile() | PLearn::NNet | [inline, static] |
| deepCopy(CopiesMap &copies) const | PLearn::NNet | [virtual] |
| deepCopyNoMap() | PLearn::Object | |
| direct_in_to_out | PLearn::NNet | |
| direct_in_to_out_weight_decay | PLearn::NNet | |
| do_not_change_params | PLearn::NNet | |
| expdir | PLearn::PLearner | |
| fillWeights(const Var &weights, bool clear_first_row) | PLearn::NNet | [protected] |
| finalize() | PLearn::PLearner | [virtual] |
| finalized | PLearn::PLearner | |
| first_class_is_junk | PLearn::NNet | |
| first_hidden_layer | PLearn::NNet | |
| first_hidden_layer_is_output | PLearn::NNet | |
| fixed_output_weights | PLearn::NNet | |
| forget() | PLearn::NNet | [virtual] |
| forget_when_training_set_changes | PLearn::PLearner | [protected] |
| getCost(const string &costname, const Var &output, const Var &target, const Var &before_transfer_func) | PLearn::NNet | [protected, virtual] |
| getExperimentDirectory() const | PLearn::PLearner | [inline] |
| getOption(const string &optionname) const | PLearn::Object | |
| getOptionList() const | PLearn::NNet | [virtual] |
| getOptionMap() const | PLearn::NNet | [virtual] |
| getOptionsToRemoteTransmit() const | PLearn::Object | [virtual] |
| getOptionsToSave() const | PLearn::Object | [virtual] |
| getOutputNames() const | PLearn::PLearner | [virtual] |
| getRemoteMethodMap() const | PLearn::NNet | [virtual] |
| getTestCostIndex(const string &costname) const | PLearn::PLearner | |
| getTestCostNames() const | PLearn::NNet | [virtual] |
| getTrainCostIndex(const string &costname) const | PLearn::PLearner | |
| getTrainCostNames() const | PLearn::NNet | [virtual] |
| getTrainingSet() const | PLearn::PLearner | [inline] |
| getTrainStatsCollector() | PLearn::PLearner | [inline] |
| getValidationSet() const | PLearn::PLearner | [inline] |
| getW1() | PLearn::NNet | [inline, virtual] |
| getW2() | PLearn::NNet | [inline, virtual] |
| getWdirect() | PLearn::NNet | [inline, virtual] |
| getWout() | PLearn::NNet | [inline, virtual] |
| hasOption(const string &optionname) const | PLearn::Object | |
| hidden_layer | PLearn::NNet | |
| hidden_transfer_func | PLearn::NNet | |
| hiddenLayer(const Var &input, const Var &weights, string transfer_func="default", VarArray *ratio_quad_weights=NULL) | PLearn::NNet | [protected] |
| info() const | PLearn::Object | [virtual] |
| inherited typedef | PLearn::NNet | [private] |
| initialization_method | PLearn::NNet | |
| initializeParams(bool set_seed=true) | PLearn::NNet | [protected, virtual] |
| initTrain() | PLearn::PLearner | [protected] |
| input | PLearn::NNet | |
| input_reconstruction_penalty | PLearn::NNet | |
| input_to_output | PLearn::NNet | [mutable] |
| inputsize() const | PLearn::PLearner | [virtual] |
| inputsize_ | PLearn::PLearner | [protected] |
| interval_maxval | PLearn::NNet | |
| interval_minval | PLearn::NNet | |
| invars | PLearn::NNet | [protected] |
| isStatefulLearner() const | PLearn::PLearner | [virtual] |
| junk_prob | PLearn::NNet | [protected] |
| L1_penalty | PLearn::NNet | |
| layer1_bias_decay | PLearn::NNet | |
| layer1_weight_decay | PLearn::NNet | |
| layer2_bias_decay | PLearn::NNet | |
| layer2_weight_decay | PLearn::NNet | |
| load(const PPath &filename) | PLearn::Object | [virtual] |
| makeDeepCopyFromShallowCopy(CopiesMap &copies) | PLearn::NNet | [virtual] |
| margin | PLearn::NNet | |
| master_sends_testset_rows | PLearn::PLearner | |
| max_bag_size | PLearn::NNet | |
| n_examples | PLearn::PLearner | [protected] |
| n_non_params_in_first_hidden_layer | PLearn::NNet | |
| n_training_bags | PLearn::NNet | [protected] |
| newread(PStream &in, unsigned int id=UINT_MAX) | PLearn::Object | |
| newwrite(PStream &out) const | PLearn::Object | [virtual] |
| nhidden | PLearn::NNet | |
| nhidden2 | PLearn::NNet | |
| NNet() | PLearn::NNet | |
| noutputs | PLearn::NNet | |
| nservers | PLearn::PLearner | |
| nstages | PLearn::PLearner | |
| nTestCosts() const | PLearn::PLearner | [virtual] |
| nTrainCosts() const | PLearn::PLearner | [virtual] |
| Object(bool call_build_=false) | PLearn::Object | |
| oldread(istream &in) | PLearn::Object | [virtual] |
| operate_on_bags | PLearn::NNet | |
| optimizer | PLearn::NNet | |
| outbias | PLearn::NNet | |
| output | PLearn::NNet | [protected] |
| output_and_target_to_cost | PLearn::NNet | [mutable] |
| output_layer_bias_decay | PLearn::NNet | |
| output_layer_weight_decay | PLearn::NNet | |
| output_transfer_func | PLearn::NNet | |
| outputsize() const | PLearn::NNet | [virtual] |
| parallelize_here | PLearn::PLearner | |
| params | PLearn::NNet | [protected] |
| paramsvalues | PLearn::NNet | |
| parseOptionName(const string &optionname, Object *&final_object, OptionList::iterator &option_iter, string &option_index) | PLearn::Object | |
| parseOptionName(const string &optionname, const Object *&final_object, OptionList::iterator &option_iter, string &option_index) const | PLearn::Object | |
| penalties | PLearn::NNet | [protected] |
| penalty_type | PLearn::NNet | |
| PLearner() | PLearn::PLearner | |
| PPointable() | PLearn::PPointable | [inline] |
| PPointable(const PPointable &other) | PLearn::PPointable | [inline] |
| predicted_input | PLearn::NNet | [protected] |
| prepareToSendResults(PStream &out, int nres) | PLearn::Object | [static] |
| processDataSet(VMat dataset) const | PLearn::PLearner | [virtual] |
| random_gen | PLearn::PLearner | [mutable, protected] |
| ratio_rank | PLearn::NNet | |
| rbf_centers | PLearn::NNet | [protected] |
| rbf_layer_size | PLearn::NNet | |
| rbf_sigmas | PLearn::NNet | [protected] |
| read(istream &in) | PLearn::Object | [virtual] |
| readOptionVal(PStream &in, const string &optionname, unsigned int id=UINT_MAX) | PLearn::Object | |
| ref() const | PLearn::PPointable | [inline] |
| remote_test(VMat testset, PP< VecStatsCollector > test_stats, bool rtestoutputs, bool rtestcosts) const | PLearn::PLearner | [virtual] |
| remote_useOnTrain() const | PLearn::PLearner | [virtual] |
| report_progress | PLearn::PLearner | |
| resetInternalState() | PLearn::PLearner | [virtual] |
| run() | PLearn::Object | [virtual] |
| sampleweight | PLearn::NNet | |
| save(const PPath &filename) const | PLearn::Object | [virtual] |
| save_trainingset_prefix | PLearn::PLearner | |
| seed_ | PLearn::PLearner | |
| setExperimentDirectory(const PPath &the_expdir) | PLearn::PLearner | [virtual] |
| setOption(const string &optionname, const string &value) | PLearn::Object | |
| setTrainingSet(VMat training_set, bool call_forget=true) | PLearn::NNet | [virtual] |
| setTrainStatsCollector(PP< VecStatsCollector > statscol) | PLearn::PLearner | [virtual] |
| setValidationSet(VMat validset) | PLearn::PLearner | [virtual] |
| stage | PLearn::PLearner | |
| store_bag_inputs | PLearn::NNet | [protected] |
| store_bag_size | PLearn::NNet | [protected] |
| sub_test(VMat testset, PP< VecStatsCollector > test_stats, bool rtestoutputs, bool rtestcosts) const | PLearn::PLearner | [virtual] |
| target | PLearn::NNet | |
| targetsize() const | PLearn::PLearner | [virtual] |
| targetsize_ | PLearn::PLearner | [protected] |
| test(VMat testset, PP< VecStatsCollector > test_stats, VMat testoutputs=0, VMat testcosts=0) const | PLearn::PLearner | [virtual] |
| test_costf | PLearn::NNet | [mutable] |
| test_costs | PLearn::NNet | [protected] |
| test_minibatch_size | PLearn::PLearner | |
| train() | PLearn::NNet | [virtual] |
| train_set | PLearn::PLearner | [protected] |
| train_stats | PLearn::PLearner | [protected] |
| training_cost | PLearn::NNet | [protected] |
| transpose_first_hidden_layer | PLearn::NNet | |
| unref() const | PLearn::PPointable | [inline] |
| usage() const | PLearn::PPointable | [inline] |
| use(VMat testset, VMat outputs) const | PLearn::PLearner | [virtual] |
| use_a_separate_random_generator_for_testing | PLearn::PLearner | |
| useOnTrain(Mat &outputs) const | PLearn::PLearner | [virtual] |
| v1 | PLearn::NNet | |
| v2 | PLearn::NNet | |
| validation_set | PLearn::PLearner | [protected] |
| verbosity | PLearn::PLearner | |
| w1 | PLearn::NNet | |
| w2 | PLearn::NNet | |
| wdirect | PLearn::NNet | |
| weight_decay | PLearn::NNet | |
| weightsize() const | PLearn::PLearner | [virtual] |
| weightsize_ | PLearn::PLearner | [protected] |
| wout | PLearn::NNet | |
| wrec | PLearn::NNet | |
| write(ostream &out) const | PLearn::Object | [virtual] |
| writeOptionVal(PStream &out, const string &optionname) const | PLearn::Object | |
| ~Object() | PLearn::Object | [virtual] |
| ~PPointable() | PLearn::PPointable | [inline, virtual] |