PLearn 0.1
PLearn::ManifoldParzen2 Member List
This is the complete list of members for PLearn::ManifoldParzen2, 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]
alphaPLearn::GaussMix
alpha_minPLearn::GaussMix
asString() const PLearn::Object [virtual]
asStringRemoteTransmit() const PLearn::Object [virtual]
b_costsPLearn::PLearner [mutable, protected]
b_inputsPLearn::PLearner [mutable, protected]
b_outputsPLearn::PLearner [mutable, protected]
b_targetsPLearn::PLearner [mutable, protected]
b_weightsPLearn::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]
centerPLearn::GaussMix
center_y_xPLearn::GaussMix [mutable, protected]
changeOption(const string &optionname, const string &value)PLearn::Object
changeOptions(const map< string, string > &name_value)PLearn::GaussMix [virtual]
chol_joint_covPLearn::GaussMix [protected]
cholesky_queuePLearn::GaussMix [mutable, protected]
classname() const PLearn::ManifoldParzen2 [virtual]
clust_imputed_missingPLearn::GaussMix [protected]
clusters_sampPLearn::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_queuePLearn::GaussMix [mutable, protected]
covariancePLearn::GaussMix [protected]
current_clusterPLearn::GaussMix [protected]
current_training_samplePLearn::GaussMix [protected]
DPLearn::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_curvePLearn::PDistribution [protected]
density(const Vec &y) const PLearn::PDistribution [virtual]
diagsPLearn::GaussMix [protected]
efficient_k_medianPLearn::GaussMix
efficient_k_median_iterPLearn::GaussMix
efficient_missingPLearn::GaussMix
eigenval_copyPLearn::ManifoldParzen2 [private]
eigenvaluesPLearn::GaussMix [protected]
eigenvalues_xPLearn::GaussMix [mutable, protected]
eigenvalues_y_xPLearn::GaussMix [mutable, protected]
eigenvectorsPLearn::GaussMix [protected]
eigenvectors_xPLearn::GaussMix [protected]
eigenvectors_y_xPLearn::GaussMix [protected]
epsilonPLearn::GaussMix
error_covariancePLearn::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
expdirPLearn::PLearner
expectation(Vec &mu) const PLearn::GaussMix [virtual]
f_eigenPLearn::GaussMix
finalize()PLearn::PLearner [virtual]
finalizedPLearn::PLearner
find_nearest_neighbor(VMat data, Vec x) const PLearn::ManifoldParzen2 [private]
forget()PLearn::GaussMix [virtual]
forget_when_training_set_changesPLearn::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_lambda0PLearn::ManifoldParzen2
H3_inversePLearn::GaussMix [protected]
hasOption(const string &optionname) const PLearn::Object
impute_missingPLearn::GaussMix
imputed_missingPLearn::GaussMix [protected]
indices_inv_queuePLearn::GaussMix [mutable, protected]
indices_queuePLearn::GaussMix [mutable, protected]
info() const PLearn::Object [virtual]
inherited typedefPLearn::ManifoldParzen2 [private]
initial_weightsPLearn::GaussMix [protected]
initTrain()PLearn::PLearner [protected]
inputsize() const PLearn::PLearner [virtual]
inputsize_PLearn::PLearner [protected]
isStatefulLearner() const PLearn::PLearner [virtual]
joint_covPLearn::GaussMix [mutable, protected]
joint_inv_covPLearn::GaussMix [mutable, protected]
kmeans(const VMat &samples, int nclust, TVec< int > &clust_idx, Mat &clust, int maxit=9999)PLearn::GaussMix [protected]
kmeans_iterationsPLearn::GaussMix
LPLearn::GaussMix
learn_muPLearn::ManifoldParzen2
load(const PPath &filename)PLearn::Object [virtual]
log_coeffPLearn::GaussMix [protected]
log_coeff_xPLearn::GaussMix [protected]
log_coeff_y_xPLearn::GaussMix [protected]
log_density(const Vec &y) const PLearn::GaussMix [virtual]
log_det_queuePLearn::GaussMix [mutable, protected]
log_likelihood_densPLearn::GaussMix [mutable, protected]
log_likelihood_post_clustPLearn::GaussMix [protected]
log_p_j_xPLearn::GaussMix [mutable, protected]
lower_boundPLearn::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_rowsPLearn::PLearner
max_samples_in_clusterPLearn::GaussMix
mean_trainingPLearn::GaussMix [protected]
min_samples_in_clusterPLearn::GaussMix
missing_patternsPLearn::GaussMix [protected]
missing_templatePLearn::GaussMix [protected]
missingExpectation(const Vec &input, Vec &mu)PLearn::GaussMix [virtual]
mu_tempPLearn::ManifoldParzen2 [mutable, private]
n_curve_pointsPLearn::PDistribution
n_eigenPLearn::GaussMix
n_eigen_computedPLearn::GaussMix [protected]
n_examplesPLearn::PLearner [protected]
n_predictedPLearn::PDistribution [mutable, protected]
n_predictorPLearn::PDistribution [mutable, protected]
ncomponentsPLearn::ManifoldParzen2
need_recomputePLearn::GaussMix [protected]
newread(PStream &in, unsigned int id=UINT_MAX)PLearn::Object
newwrite(PStream &out) const PLearn::Object [virtual]
nneighborsPLearn::ManifoldParzen2
no_missing_changePLearn::GaussMix [protected]
nsamplesPLearn::GaussMix [protected]
nserversPLearn::PLearner
nstagesPLearn::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_reorderedPLearn::GaussMix [protected]
outputs_defPLearn::PDistribution
outputsize() const PLearn::ManifoldParzen2 [virtual]
p_j_xPLearn::GaussMix [mutable, protected]
parallelize_herePLearn::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
posteriorsPLearn::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_partPLearn::PDistribution [mutable, protected]
predicted_sizePLearn::PDistribution [protected]
predictor_partPLearn::PDistribution [mutable, protected]
predictor_sizePLearn::PDistribution [protected]
prepareToSendResults(PStream &out, int nres)PLearn::Object [static]
previous_predictor_part_had_missingPLearn::GaussMix [mutable, protected]
previous_training_samplePLearn::GaussMix [protected]
processDataSet(VMat dataset) const PLearn::PLearner [virtual]
ptimerPLearn::GaussMix [protected]
random_genPLearn::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_setPLearn::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_progressPLearn::PLearner
resetGenerator(long g_seed)PLearn::PDistribution [virtual]
resetInternalState()PLearn::PLearner [virtual]
resizeDataBeforeTraining()PLearn::GaussMix [protected]
resizeDataBeforeUsing()PLearn::GaussMix [protected]
rowPLearn::ManifoldParzen2 [mutable, private]
run()PLearn::Object [virtual]
sample_to_path_indexPLearn::GaussMix [protected]
sample_to_templatePLearn::GaussMix [protected]
save(const PPath &filename) const PLearn::Object [virtual]
save_trainingset_prefixPLearn::PLearner
scale_factorPLearn::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]
sigmaPLearn::GaussMix
sigma_minPLearn::GaussMix
spanning_can_freePLearn::GaussMix [protected]
spanning_pathPLearn::GaussMix [protected]
spanning_use_previousPLearn::GaussMix [protected]
splitCond(const Vec &input) const PLearn::PDistribution [protected]
stagePLearn::PLearner
stage_joint_cov_computedPLearn::GaussMix [protected]
stage_replacedPLearn::GaussMix [protected]
stddev_trainingPLearn::GaussMix [protected]
store_covPLearn::PDistribution [mutable, protected]
store_expectPLearn::PDistribution [mutable, protected]
store_resultPLearn::PDistribution [mutable, protected]
sub_test(VMat testset, PP< VecStatsCollector > test_stats, bool rtestoutputs, bool rtestcosts) const PLearn::PLearner [virtual]
sum_of_posteriorsPLearn::GaussMix [protected]
survival_fn(const Vec &y) const PLearn::GaussMix [virtual]
t_rowPLearn::ManifoldParzen2 [mutable, private]
targetsize() const PLearn::PLearner [virtual]
targetsize_PLearn::PLearner [protected]
temp_eigvPLearn::ManifoldParzen2 [mutable, private]
test(VMat testset, PP< VecStatsCollector > test_stats, VMat testoutputs=0, VMat testcosts=0) const PLearn::PLearner [virtual]
test_minibatch_sizePLearn::PLearner
train()PLearn::ManifoldParzen2 [virtual]
train_setPLearn::PLearner [protected]
train_statsPLearn::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]
typePLearn::GaussMix
type_idPLearn::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_weightsPLearn::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_boundPLearn::PDistribution
usage() const PLearn::PPointable [inline]
use(VMat testset, VMat outputs) const PLearn::PLearner [virtual]
use_a_separate_random_generator_for_testingPLearn::PLearner
use_last_eigenvalPLearn::ManifoldParzen2
useOnTrain(Mat &outputs) const PLearn::PLearner [virtual]
validation_setPLearn::PLearner [protected]
variance(Mat &cov) const PLearn::GaussMix [virtual]
verbosityPLearn::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_centeredPLearn::GaussMix [mutable, protected]
y_x_matPLearn::GaussMix [protected]
~Object()PLearn::Object [virtual]
~PPointable()PLearn::PPointable [inline, virtual]
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Defines