, including all inherited members.
| _classname_() | PLearn::ManifoldParzen2 | [static] |
| _getOptionList_() | PLearn::ManifoldParzen2 | [static] |
| _getRemoteMethodMap_() | PLearn::ManifoldParzen2 | [static] |
| _isa_(const Object *o) | PLearn::ManifoldParzen2 | [static] |
| _new_instance_for_typemap_() | PLearn::ManifoldParzen2 | [static] |
| _static_initialize_() | PLearn::ManifoldParzen2 | [static] |
| _static_initializer_ | PLearn::ManifoldParzen2 | [static] |
| addToCovariance(const Vec &y, int j, const Mat &cov, real post) | PLearn::GaussMix | [protected] |
| alpha | PLearn::GaussMix | |
| alpha_min | PLearn::GaussMix | |
| 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] |
| batchComputeOutputAndConfidence(VMat inputs, real probability, VMat outputs_and_confidence) const | PLearn::PLearner | [virtual] |
| build() | PLearn::ManifoldParzen2 | [virtual] |
| build_() | PLearn::ManifoldParzen2 | [private] |
| build_from_train_set() | PLearn::PLearner | [inline, protected, virtual] |
| call(const string &methodname, int nargs, PStream &io) | PLearn::Object | [virtual] |
| cdf(const Vec &y) const | PLearn::GaussMix | [virtual] |
| center | PLearn::GaussMix | |
| center_y_x | PLearn::GaussMix | [mutable, protected] |
| changeOption(const string &optionname, const string &value) | PLearn::Object | |
| changeOptions(const map< string, string > &name_value) | PLearn::GaussMix | [virtual] |
| chol_joint_cov | PLearn::GaussMix | [protected] |
| cholesky_queue | PLearn::GaussMix | [mutable, protected] |
| classname() const | PLearn::ManifoldParzen2 | [virtual] |
| clust_imputed_missing | PLearn::GaussMix | [protected] |
| clusters_samp | PLearn::GaussMix | [protected] |
| computeAllLogLikelihoods(const Vec &sample, const Vec &log_like) | PLearn::GaussMix | [protected] |
| 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::PDistribution | [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 | |
| computeLogLikelihood(const Vec &y, int j, bool is_predictor=false) const | PLearn::GaussMix | [protected] |
| computeMeansAndCovariances() | PLearn::GaussMix | [protected, virtual] |
| computeMixtureWeights(bool allow_replace=true) | PLearn::GaussMix | [protected] |
| computeOutput(const Vec &input, Vec &output) const | PLearn::ManifoldParzen2 | [virtual] |
| computeOutputAndCosts(const Vec &input, const Vec &target, Vec &output, Vec &costs) const | PLearn::PLearner | [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] |
| computePosteriors() | PLearn::GaussMix | [protected, virtual] |
| cond_var_inv_queue | PLearn::GaussMix | [mutable, protected] |
| covariance | PLearn::GaussMix | [protected] |
| current_cluster | PLearn::GaussMix | [protected] |
| current_training_sample | PLearn::GaussMix | [protected] |
| D | PLearn::GaussMix | [protected] |
| declareMethods(RemoteMethodMap &rmm) | PLearn::PDistribution | [protected, static] |
| declareOptions(OptionList &ol) | PLearn::ManifoldParzen2 | [protected, static] |
| declaringFile() | PLearn::ManifoldParzen2 | [inline, static] |
| deepCopy(CopiesMap &copies) const | PLearn::ManifoldParzen2 | [virtual] |
| deepCopyNoMap() | PLearn::Object | |
| delta_curve | PLearn::PDistribution | [protected] |
| density(const Vec &y) const | PLearn::PDistribution | [virtual] |
| diags | PLearn::GaussMix | [protected] |
| efficient_k_median | PLearn::GaussMix | |
| efficient_k_median_iter | PLearn::GaussMix | |
| efficient_missing | PLearn::GaussMix | |
| eigenval_copy | PLearn::ManifoldParzen2 | [private] |
| eigenvalues | PLearn::GaussMix | [protected] |
| eigenvalues_x | PLearn::GaussMix | [mutable, protected] |
| eigenvalues_y_x | PLearn::GaussMix | [mutable, protected] |
| eigenvectors | PLearn::GaussMix | [protected] |
| eigenvectors_x | PLearn::GaussMix | [protected] |
| eigenvectors_y_x | PLearn::GaussMix | [protected] |
| epsilon | PLearn::GaussMix | |
| error_covariance | PLearn::GaussMix | [protected] |
| evaluate(const Vec x1, const Vec x2, real scale=1) | PLearn::ManifoldParzen2 | |
| evaluate_i_j(int i, int j, real scale=1) | PLearn::ManifoldParzen2 | |
| expdir | PLearn::PLearner | |
| expectation(Vec &mu) const | PLearn::GaussMix | [virtual] |
| f_eigen | PLearn::GaussMix | |
| finalize() | PLearn::PLearner | [virtual] |
| finalized | PLearn::PLearner | |
| find_nearest_neighbor(VMat data, Vec x) const | PLearn::ManifoldParzen2 | [private] |
| forget() | PLearn::GaussMix | [virtual] |
| forget_when_training_set_changes | PLearn::PLearner | [protected] |
| GaussMix() | PLearn::GaussMix | |
| generate(Vec &s) const | PLearn::GaussMix | [virtual] |
| generateFromGaussian(Vec &s, int given_gaussian) const | PLearn::GaussMix | [protected] |
| generateJoint(Vec &xy) | PLearn::PDistribution | [virtual] |
| generateJoint(Vec &x, Vec &y) | PLearn::PDistribution | |
| generateN(const Mat &Y) const | PLearn::PDistribution | [virtual] |
| generatePredicted(Vec &y) | PLearn::PDistribution | [virtual] |
| generatePredictor(Vec &x) | PLearn::PDistribution | [virtual] |
| generatePredictorGivenPredicted(Vec &x, const Vec &y) | PLearn::PDistribution | [virtual] |
| getExperimentDirectory() const | PLearn::PLearner | [inline] |
| getInitialWeightsFrom(const VMat &vmat) | PLearn::GaussMix | [protected] |
| getNPredicted() const | PLearn::PDistribution | [inline] |
| getNPredictor() const | PLearn::PDistribution | [inline] |
| getOption(const string &optionname) const | PLearn::Object | |
| getOptionList() const | PLearn::ManifoldParzen2 | [virtual] |
| getOptionMap() const | PLearn::ManifoldParzen2 | [virtual] |
| getOptionsToRemoteTransmit() const | PLearn::Object | [virtual] |
| getOptionsToSave() const | PLearn::Object | [virtual] |
| getOutputNames() const | PLearn::PLearner | [virtual] |
| getRemoteMethodMap() const | PLearn::ManifoldParzen2 | [virtual] |
| getTestCostIndex(const string &costname) const | PLearn::PLearner | |
| getTestCostNames() const | PLearn::PDistribution | [virtual] |
| getTrainCostIndex(const string &costname) const | PLearn::PLearner | |
| getTrainCostNames() const | PLearn::GaussMix | [virtual] |
| getTrainingSet() const | PLearn::PLearner | [inline] |
| getTrainStatsCollector() | PLearn::PLearner | [inline] |
| getValidationSet() const | PLearn::PLearner | [inline] |
| global_lambda0 | PLearn::ManifoldParzen2 | |
| H3_inverse | PLearn::GaussMix | [protected] |
| hasOption(const string &optionname) const | PLearn::Object | |
| impute_missing | PLearn::GaussMix | |
| imputed_missing | PLearn::GaussMix | [protected] |
| indices_inv_queue | PLearn::GaussMix | [mutable, protected] |
| indices_queue | PLearn::GaussMix | [mutable, protected] |
| info() const | PLearn::Object | [virtual] |
| inherited typedef | PLearn::ManifoldParzen2 | [private] |
| initial_weights | PLearn::GaussMix | [protected] |
| initTrain() | PLearn::PLearner | [protected] |
| inputsize() const | PLearn::PLearner | [virtual] |
| inputsize_ | PLearn::PLearner | [protected] |
| isStatefulLearner() const | PLearn::PLearner | [virtual] |
| joint_cov | PLearn::GaussMix | [mutable, protected] |
| joint_inv_cov | PLearn::GaussMix | [mutable, protected] |
| kmeans(const VMat &samples, int nclust, TVec< int > &clust_idx, Mat &clust, int maxit=9999) | PLearn::GaussMix | [protected] |
| kmeans_iterations | PLearn::GaussMix | |
| L | PLearn::GaussMix | |
| learn_mu | PLearn::ManifoldParzen2 | |
| load(const PPath &filename) | PLearn::Object | [virtual] |
| log_coeff | PLearn::GaussMix | [protected] |
| log_coeff_x | PLearn::GaussMix | [protected] |
| log_coeff_y_x | PLearn::GaussMix | [protected] |
| log_density(const Vec &y) const | PLearn::GaussMix | [virtual] |
| log_det_queue | PLearn::GaussMix | [mutable, protected] |
| log_likelihood_dens | PLearn::GaussMix | [mutable, protected] |
| log_likelihood_post_clust | PLearn::GaussMix | [protected] |
| log_p_j_x | PLearn::GaussMix | [mutable, protected] |
| lower_bound | PLearn::PDistribution | |
| makeDeepCopyFromShallowCopy(CopiesMap &copies) | PLearn::ManifoldParzen2 | [virtual] |
| ManifoldParzen2() | PLearn::ManifoldParzen2 | |
| ManifoldParzen2(int the_nneighbors, int the_ncomponents, bool use_last_eigenvalue=true, real scale_factor=1) | PLearn::ManifoldParzen2 | |
| master_sends_testset_rows | PLearn::PLearner | |
| max_samples_in_cluster | PLearn::GaussMix | |
| mean_training | PLearn::GaussMix | [protected] |
| min_samples_in_cluster | PLearn::GaussMix | |
| missing_patterns | PLearn::GaussMix | [protected] |
| missing_template | PLearn::GaussMix | [protected] |
| missingExpectation(const Vec &input, Vec &mu) | PLearn::GaussMix | [virtual] |
| mu_temp | PLearn::ManifoldParzen2 | [mutable, private] |
| n_curve_points | PLearn::PDistribution | |
| n_eigen | PLearn::GaussMix | |
| n_eigen_computed | PLearn::GaussMix | [protected] |
| n_examples | PLearn::PLearner | [protected] |
| n_predicted | PLearn::PDistribution | [mutable, protected] |
| n_predictor | PLearn::PDistribution | [mutable, protected] |
| ncomponents | PLearn::ManifoldParzen2 | |
| need_recompute | PLearn::GaussMix | [protected] |
| newread(PStream &in, unsigned int id=UINT_MAX) | PLearn::Object | |
| newwrite(PStream &out) const | PLearn::Object | [virtual] |
| nneighbors | PLearn::ManifoldParzen2 | |
| no_missing_change | PLearn::GaussMix | [protected] |
| nsamples | PLearn::GaussMix | [protected] |
| 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] |
| original_to_reordered | PLearn::GaussMix | [protected] |
| outputs_def | PLearn::PDistribution | |
| outputsize() const | PLearn::ManifoldParzen2 | [virtual] |
| p_j_x | PLearn::GaussMix | [mutable, protected] |
| parallelize_here | PLearn::PLearner | |
| 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 | |
| PDistribution() | PLearn::PDistribution | |
| PLearner() | PLearn::PLearner | |
| posteriors | PLearn::GaussMix | [protected] |
| PPointable() | PLearn::PPointable | [inline] |
| PPointable(const PPointable &other) | PLearn::PPointable | [inline] |
| precomputeAllGaussianLogCoefficients() | PLearn::GaussMix | [protected] |
| precomputeGaussianLogCoefficient(const Vec &eigenvals, int dimension) const | PLearn::GaussMix | [protected] |
| predicted_part | PLearn::PDistribution | [mutable, protected] |
| predicted_size | PLearn::PDistribution | [protected] |
| predictor_part | PLearn::PDistribution | [mutable, protected] |
| predictor_size | PLearn::PDistribution | [protected] |
| prepareToSendResults(PStream &out, int nres) | PLearn::Object | [static] |
| previous_predictor_part_had_missing | PLearn::GaussMix | [mutable, protected] |
| previous_training_sample | PLearn::GaussMix | [protected] |
| processDataSet(VMat dataset) const | PLearn::PLearner | [virtual] |
| ptimer | PLearn::GaussMix | [protected] |
| random_gen | PLearn::PLearner | [mutable, 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] |
| reference_set | PLearn::ManifoldParzen2 | [mutable, private] |
| remote_generate() | PLearn::PDistribution | |
| remote_test(VMat testset, PP< VecStatsCollector > test_stats, bool rtestoutputs, bool rtestcosts) const | PLearn::PLearner | [virtual] |
| remote_useOnTrain() const | PLearn::PLearner | [virtual] |
| replaceGaussian(int j) | PLearn::GaussMix | [protected] |
| report_progress | PLearn::PLearner | |
| resetGenerator(long g_seed) | PLearn::PDistribution | [virtual] |
| resetInternalState() | PLearn::PLearner | [virtual] |
| resizeDataBeforeTraining() | PLearn::GaussMix | [protected] |
| resizeDataBeforeUsing() | PLearn::GaussMix | [protected] |
| row | PLearn::ManifoldParzen2 | [mutable, private] |
| run() | PLearn::Object | [virtual] |
| sample_to_path_index | PLearn::GaussMix | [protected] |
| sample_to_template | PLearn::GaussMix | [protected] |
| save(const PPath &filename) const | PLearn::Object | [virtual] |
| save_trainingset_prefix | PLearn::PLearner | |
| scale_factor | PLearn::ManifoldParzen2 | |
| seed_ | PLearn::PLearner | |
| setExperimentDirectory(const PPath &the_expdir) | PLearn::PLearner | [virtual] |
| setOption(const string &optionname, const string &value) | PLearn::Object | |
| setPredictor(const Vec &predictor, bool call_parent=true) const | PLearn::GaussMix | [virtual] |
| setPredictorPredictedSizes(int the_predictor_size, int the_predicted_size, bool call_parent=true) | PLearn::GaussMix | [protected, virtual] |
| setPredictorPredictedSizes_const() const | PLearn::GaussMix | [protected] |
| setTrainingSet(VMat training_set, bool call_forget=true) | PLearn::GaussMix | [virtual] |
| setTrainStatsCollector(PP< VecStatsCollector > statscol) | PLearn::PLearner | [virtual] |
| setValidationSet(VMat validset) | PLearn::PLearner | [virtual] |
| sigma | PLearn::GaussMix | |
| sigma_min | PLearn::GaussMix | |
| spanning_can_free | PLearn::GaussMix | [protected] |
| spanning_path | PLearn::GaussMix | [protected] |
| spanning_use_previous | PLearn::GaussMix | [protected] |
| splitCond(const Vec &input) const | PLearn::PDistribution | [protected] |
| stage | PLearn::PLearner | |
| stage_joint_cov_computed | PLearn::GaussMix | [protected] |
| stage_replaced | PLearn::GaussMix | [protected] |
| stddev_training | PLearn::GaussMix | [protected] |
| store_cov | PLearn::PDistribution | [mutable, protected] |
| store_expect | PLearn::PDistribution | [mutable, protected] |
| store_result | PLearn::PDistribution | [mutable, protected] |
| sub_test(VMat testset, PP< VecStatsCollector > test_stats, bool rtestoutputs, bool rtestcosts) const | PLearn::PLearner | [virtual] |
| sum_of_posteriors | PLearn::GaussMix | [protected] |
| survival_fn(const Vec &y) const | PLearn::GaussMix | [virtual] |
| t_row | PLearn::ManifoldParzen2 | [mutable, private] |
| targetsize() const | PLearn::PLearner | [virtual] |
| targetsize_ | PLearn::PLearner | [protected] |
| temp_eigv | PLearn::ManifoldParzen2 | [mutable, private] |
| test(VMat testset, PP< VecStatsCollector > test_stats, VMat testoutputs=0, VMat testcosts=0) const | PLearn::PLearner | [virtual] |
| test_minibatch_size | PLearn::PLearner | |
| train() | PLearn::ManifoldParzen2 | [virtual] |
| train_set | PLearn::PLearner | [protected] |
| train_stats | PLearn::PLearner | [protected] |
| traverse_tree(TVec< int > &path, TVec< bool > &span_can_free, TVec< bool > &span_use_previous, bool free_previous, bool use_previous, int index_node, int previous_node, const TVec< int > &parent, const TVec< TVec< int > > &children, const TVec< int > &message_up, const TVec< int > &message_down) | PLearn::GaussMix | [protected, static] |
| type | PLearn::GaussMix | |
| type_id | PLearn::GaussMix | [protected] |
| unknownOutput(char def, const Vec &input, Vec &output, int &k) const | PLearn::GaussMix | [protected, virtual] |
| unref() const | PLearn::PPointable | [inline] |
| updateCholeskyFromPrevious(const Mat &chol_previous, Mat &chol_updated, const Mat &full_matrix, const TVec< int > &indices_previous, const TVec< int > &indices_updated) const | PLearn::GaussMix | [protected] |
| updated_weights | PLearn::GaussMix | [protected] |
| updateInverseVarianceFromPrevious(const Mat &src, Mat &dst, const Mat &full, const TVec< int > &ind_src, const TVec< int > &ind_dst, real *src_log_det=0, real *dst_log_det=0) const | PLearn::GaussMix | [protected] |
| updateSampleWeights() | PLearn::GaussMix | [protected] |
| upper_bound | PLearn::PDistribution | |
| usage() const | PLearn::PPointable | [inline] |
| use(VMat testset, VMat outputs) const | PLearn::PLearner | [virtual] |
| use_a_separate_random_generator_for_testing | PLearn::PLearner | |
| use_last_eigenval | PLearn::ManifoldParzen2 | |
| useOnTrain(Mat &outputs) const | PLearn::PLearner | [virtual] |
| validation_set | PLearn::PLearner | [protected] |
| variance(Mat &cov) const | PLearn::GaussMix | [virtual] |
| verbosity | PLearn::PLearner | |
| weightsize() const | PLearn::PLearner | [virtual] |
| weightsize_ | PLearn::PLearner | [protected] |
| write(ostream &out) const | PLearn::Object | [virtual] |
| writeOptionVal(PStream &out, const string &optionname) const | PLearn::Object | |
| y_centered | PLearn::GaussMix | [mutable, protected] |
| y_x_mat | PLearn::GaussMix | [protected] |
| ~Object() | PLearn::Object | [virtual] |
| ~PPointable() | PLearn::PPointable | [inline, virtual] |