| _classname_() | PLearn::Object | [static] |
| _getOptionList_() | PLearn::Object | [static] |
| _isa_(Object *o) | PLearn::Object | [static] |
| _new_instance_for_typemap_() | PLearn::Object | [static] |
| _static_initialize_() | PLearn::Object | [static] |
| _static_initializer_ | PLearn::Object | [static] |
| appendMeasurer(Measurer &measurer) | PLearn::Learner | [inline] |
| apply(const VMat &data, VMat outputs) | PLearn::Learner | [virtual] |
| applyAndComputeCosts(const VMat &data, VMat outputs, VMat costs) | PLearn::Learner | [virtual] |
| applyAndComputeCostsOnTestMat(const VMat &test_set, int i, const Mat &output_block, const Mat &cost_block) | PLearn::Learner | [virtual] |
| avg_objective | PLearn::Learner | |
| avgsq_objective | PLearn::Learner | |
| basename() const | PLearn::Learner | |
| best_step | PLearn::Learner | |
| build() | PLearn::Distribution | [virtual] |
| call(const string &methodname, int nargs, PStream &in_parameters, PStream &out_results) | PLearn::Object | [virtual] |
| cdf(const Vec &x) const | PLearn::EmpiricalDistribution | [virtual] |
| changeOption(const string &optionname, const string &value) | PLearn::Object | |
| changeOptions(const map< string, string > &name_value) | PLearn::Object | [virtual] |
| classname() const | PLearn::Object | [virtual] |
| computeCost(const Vec &input, const Vec &target, const Vec &output, const Vec &cost) | PLearn::Learner | [virtual] |
| computeCosts(const VVec &input, VVec &target, VVec &weight, Vec &costs) | PLearn::Learner | [virtual] |
| computeCosts(const VMat &data, VMat costs) | PLearn::Learner | [virtual] |
| computeCostsFromOutputs(const VVec &input, const Vec &output, const VVec &target, const VVec &weight, Vec &costs) | PLearn::Learner | [virtual] |
| computeLeaveOneOutCosts(const VMat &data, VMat costs) | PLearn::Learner | [virtual] |
| computeLeaveOneOutCosts(const VMat &data, VMat costsmat, CostFunc costf) | PLearn::Learner | [virtual] |
| computeOutput(const VVec &input, Vec &output) | PLearn::Learner | [virtual] |
| computeOutputAndCosts(const VVec &input, VVec &target, const VVec &weight, Vec &output, Vec &costs) | PLearn::Learner | [virtual] |
| computeTestStatistics(const VMat &costs) | PLearn::Learner | |
| costNames() const | PLearn::Learner | [virtual] |
| costsize() const | PLearn::Learner | [virtual] |
| current_sample_x | PLearn::EmpiricalDistribution | [mutable] |
| current_sample_y | PLearn::EmpiricalDistribution | [mutable] |
| data | PLearn::EmpiricalDistribution | [protected] |
| declareOptions(OptionList &ol) | PLearn::EmpiricalDistribution | [protected, static] |
| deepCopy(CopiesMap &copies) const | PLearn::Object | [virtual] |
| default_vlog() | PLearn::Learner | [static] |
| density(const Vec &x) const | PLearn::Distribution | [virtual] |
| distributed_ | PLearn::Learner | [protected] |
| Distribution() | PLearn::Distribution | |
| dont_parallelize | PLearn::Learner | |
| each_cpu_saves_its_errors | PLearn::Learner | [protected] |
| earlystop_max_degradation | PLearn::Learner | |
| earlystop_max_degraded_steps | PLearn::Learner | |
| earlystop_min_improvement | PLearn::Learner | |
| earlystop_min_value | PLearn::Learner | |
| earlystop_minval | PLearn::Learner | |
| earlystop_previousval | PLearn::Learner | [protected] |
| earlystop_relative_changes | PLearn::Learner | |
| earlystop_save_best | PLearn::Learner | |
| earlystop_testresultindex | PLearn::Learner | |
| earlystop_testsetnum | PLearn::Learner | |
| EmpiricalDistribution() | PLearn::EmpiricalDistribution | |
| EmpiricalDistribution(int inputsize, bool random_sample_=true) | PLearn::EmpiricalDistribution | |
| epoch() const | PLearn::Learner | [inline] |
| epoch_ | PLearn::Learner | [protected] |
| expdir | PLearn::Learner | [protected] |
| expectation() const | PLearn::EmpiricalDistribution | [virtual] |
| experiment_name | PLearn::Learner | |
| flip | PLearn::EmpiricalDistribution | [mutable] |
| force_saving_on_all_processes | PLearn::Learner | [static] |
| forget() | PLearn::Learner | [virtual] |
| freeTestResultsStreams() | PLearn::Learner | [protected] |
| generate(Vec &x) const | PLearn::EmpiricalDistribution | [virtual] |
| getExperimentDirectory() const | PLearn::Learner | [inline] |
| getOption(const string &optionname) const | PLearn::Object | |
| getOptionList() const | PLearn::Object | [virtual] |
| getOptionsToSave() const | PLearn::Object | [virtual] |
| getTestDuringTrain() const | PLearn::Learner | [inline] |
| getTestResultsStream(int k) | PLearn::Learner | [protected] |
| getTrainCost() | PLearn::Learner | [inline] |
| getTrainingSet() | PLearn::Learner | [inline] |
| getTrainObjectiveStream() | PLearn::Learner | [protected] |
| info() const | PLearn::Object | [virtual] |
| inherited typedef | PLearn::EmpiricalDistribution | [protected] |
| inputsize() const | PLearn::Learner | [inline] |
| inputsize_ | PLearn::Learner | |
| Learner(int the_inputsize=0, int the_targetsize=0, int the_outputsize=0) | PLearn::Learner | |
| length | PLearn::EmpiricalDistribution | |
| load(const string &filename="") | PLearn::Learner | [virtual] |
| log_density(const Vec &x) const | PLearn::EmpiricalDistribution | [virtual] |
| makeDeepCopyFromShallowCopy(CopiesMap &copies) | PLearn::EmpiricalDistribution | [virtual] |
| PLearn::Distribution::makeDeepCopyFromShallowCopy(map< const void *, void * > &copies) | PLearn::Distribution | [virtual] |
| measure(int step, const Vec &costs) | PLearn::Learner | [virtual] |
| PLearn::Measurer::measure(int t) | PLearn::Measurer | [inline, virtual] |
| measure_cpu_time_first | PLearn::Learner | [protected] |
| measurers | PLearn::Learner | [protected] |
| minibatch_size | PLearn::Learner | |
| newread(PStream &in) | PLearn::Object | |
| newtest(VMat testset, VecStatsCollector &test_stats, VMat testoutputs=0, VMat testcosts=0) | PLearn::Learner | [virtual] |
| newtrain(VecStatsCollector &train_stats) | PLearn::Learner | [virtual] |
| newwrite(PStream &out) const | PLearn::Object | |
| Object() | PLearn::Object | |
| objectiveout | PLearn::Learner | |
| oldread(istream &in) | PLearn::Learner | [virtual] |
| oldwrite(ostream &out) const | PLearn::Learner | [virtual] |
| openTestResultsStreams() | PLearn::Learner | [protected] |
| openTrainObjectiveStream() | PLearn::Learner | [protected] |
| options | PLearn::Learner | |
| outputResultLineToFile(const string &filename, const Vec &results, bool append, const string &names) | PLearn::Learner | [protected] |
| outputsize() const | PLearn::Learner | [inline] |
| outputsize_ | PLearn::Learner | |
| PLEARN_DECLARE_ABSTRACT_OBJECT(Learner) | PLearn::Learner | |
| PLEARN_DECLARE_OBJECT(EmpiricalDistribution) | PLearn::EmpiricalDistribution | |
| PLearn::Distribution::PLEARN_DECLARE_OBJECT(Distribution) | PLearn::Distribution | |
| PPointable() | PLearn::PPointable | [inline] |
| PPointable(const PPointable &other) | PLearn::PPointable | [inline] |
| prepareToSendResults(PStream &out, int nres) | PLearn::Object | [inline, protected] |
| print(ostream &out) const | PLearn::Object | [virtual] |
| random_sample | PLearn::EmpiricalDistribution | |
| read(istream &in) | PLearn::Object | [virtual] |
| readOptionVal(PStream &in, const string &optionname) | PLearn::Object | |
| ref() const | PLearn::PPointable | [inline] |
| report_test_progress_every | PLearn::Learner | |
| run() | PLearn::Object | [virtual] |
| save(const string &filename="") const | PLearn::Learner | [virtual] |
| save_at_every_epoch | PLearn::Learner | |
| save_objective | PLearn::Learner | |
| setEarlyStopping(int which_testset, int which_testresult, real max_degradation, real min_value=-FLT_MAX, real min_improvement=0, bool relative_changes=true, bool save_best=true, int max_degraded_steps=-1) | PLearn::Learner | |
| setExperimentDirectory(const string &the_expdir) | PLearn::Learner | [virtual] |
| setModel(const Vec &new_options) | PLearn::Learner | [virtual] |
| setOption(const string &optionname, const string &value) | PLearn::Object | |
| setTestCostFunctions(Array< CostFunc > costfunctions) | PLearn::Learner | [inline] |
| setTestDuringTrain(ostream &testout, int every, Array< VMat > testsets) | PLearn::Learner | [virtual] |
| setTestDuringTrain(Array< VMat > testsets) | PLearn::Learner | [virtual] |
| setTestStatistics(StatsItArray statistics) | PLearn::Learner | [inline] |
| setTrainCost(Vec &cost) | PLearn::Learner | [inline, protected] |
| setTrainingSet(VMat training_set) | PLearn::Learner | [inline, virtual] |
| stop_if_wanted() | PLearn::Learner | [virtual] |
| survival_fn(const Vec &x) const | PLearn::EmpiricalDistribution | [virtual] |
| targetsize() const | PLearn::Learner | [inline] |
| targetsize_ | PLearn::Learner | |
| test(VMat test_set, const string &save_test_outputs="", const string &save_test_costs="") | PLearn::Learner | [virtual] |
| test_costfuncs | PLearn::Learner | |
| test_every | PLearn::Learner | |
| test_results_streams | PLearn::Learner | [protected] |
| test_sets | PLearn::Learner | |
| test_statistics | PLearn::Learner | |
| testout | PLearn::Learner | |
| testResultsNames() const | PLearn::Learner | [virtual] |
| tmpvec | PLearn::Learner | [protected] |
| train(VMat training_set) | PLearn::EmpiricalDistribution | [virtual] |
| PLearn::Learner::train(VMat training_set, VMat accept_prob, real max_accept_prob=1.0, VMat weights=VMat()) | PLearn::Learner | [inline, virtual] |
| train_cost | PLearn::Learner | [protected] |
| train_objective_stream | PLearn::Learner | [protected] |
| train_set | PLearn::Learner | |
| trainObjectiveNames() const | PLearn::Learner | [virtual] |
| unref() const | PLearn::PPointable | [inline] |
| usage() const | PLearn::PPointable | [inline] |
| use(const Vec &input, Vec &output) | PLearn::Distribution | [virtual] |
| PLearn::Learner::use(const Mat &inputs, Mat outputs) | PLearn::Learner | [inline, virtual] |
| use_file_if_bigger | PLearn::Learner | [static] |
| use_returns_what | PLearn::Distribution | |
| useAndCost(const Vec &input, const Vec &target, Vec output, Vec cost) | PLearn::Learner | [virtual] |
| useAndCostOnTestVec(const VMat &test_set, int i, const Vec &output, const Vec &cost) | PLearn::Learner | [virtual] |
| variance() const | PLearn::EmpiricalDistribution | [virtual] |
| vec_input | PLearn::Learner | |
| vlog | PLearn::Learner | |
| weightsize() const | PLearn::Learner | [inline] |
| weightsize_ | PLearn::Learner | |
| write(ostream &out) const | PLearn::Object | [virtual] |
| writeOptionVal(PStream &out, const string &optionname) const | PLearn::Object | |
| ~Learner() | PLearn::Learner | [virtual] |
| ~Measurer() | PLearn::Measurer | [virtual] |
| ~Object() | PLearn::Object | [virtual] |
| ~PPointable() | PLearn::PPointable | [inline, virtual] |
