PLearn 0.1
PLearn::GaussianProcessRegressor Member List
This is the complete list of members for PLearn::GaussianProcessRegressor, including all inherited members.
_classname_()PLearn::GaussianProcessRegressor [static]
_classname_()PLearn::GaussianProcessRegressor [static]
_getOptionList_()PLearn::GaussianProcessRegressor [static]
_getOptionList_()PLearn::GaussianProcessRegressor [static]
_getRemoteMethodMap_()PLearn::GaussianProcessRegressor [static]
_getRemoteMethodMap_()PLearn::GaussianProcessRegressor [static]
_isa_(const Object *o)PLearn::GaussianProcessRegressor [static]
_isa_(const Object *o)PLearn::GaussianProcessRegressor [static]
_new_instance_for_typemap_()PLearn::GaussianProcessRegressor [static]
_new_instance_for_typemap_()PLearn::GaussianProcessRegressor [static]
_static_initialize_()PLearn::GaussianProcessRegressor [static]
_static_initialize_()PLearn::GaussianProcessRegressor [static]
_static_initializer_PLearn::GaussianProcessRegressor [static]
AlgoExact enum valuePLearn::GaussianProcessRegressor [protected]
AlgoProjectedProcess enum valuePLearn::GaussianProcessRegressor [protected]
alphaPLearn::GaussianProcessRegressor
asString() const PLearn::Object [virtual]
asStringRemoteTransmit() const PLearn::Object [virtual]
PLearn::b_costsPLearn::PLearner [mutable, protected]
PLearn::PConditionalDistribution::b_costsPLearn::PLearner [mutable, protected]
PLearn::b_inputsPLearn::PLearner [mutable, protected]
PLearn::PConditionalDistribution::b_inputsPLearn::PLearner [mutable, protected]
PLearn::b_outputsPLearn::PLearner [mutable, protected]
PLearn::PConditionalDistribution::b_outputsPLearn::PLearner [mutable, protected]
PLearn::b_targetsPLearn::PLearner [mutable, protected]
PLearn::PConditionalDistribution::b_targetsPLearn::PLearner [mutable, protected]
PLearn::b_weightsPLearn::PLearner [mutable, protected]
PLearn::PConditionalDistribution::b_weightsPLearn::PLearner [mutable, protected]
batchComputeOutputAndConfidence(VMat inputs, real probability, VMat outputs_and_confidence) const PLearn::PLearner [virtual]
BayesianCost()PLearn::GaussianProcessRegressor [protected]
build()PLearn::GaussianProcessRegressor [virtual]
build()PLearn::GaussianProcessRegressor [virtual]
build_()PLearn::GaussianProcessRegressor [private]
build_()PLearn::GaussianProcessRegressor [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::PDistribution [virtual]
PLearn::changeOption(const string &optionname, const string &value)PLearn::Object
PLearn::PConditionalDistribution::changeOption(const string &optionname, const string &value)PLearn::Object
changeOptions(const map< string, string > &name_value)PLearn::Object [virtual]
classname() const PLearn::GaussianProcessRegressor [virtual]
classname() const PLearn::GaussianProcessRegressor [virtual]
computeConfidenceFromOutput(const Vec &input, const Vec &output, real probability, TVec< pair< real, real > > &intervals) const PLearn::GaussianProcessRegressor [virtual]
computeCostsFromOutputs(const Vec &input, const Vec &output, const Vec &target, Vec &costs) const PLearn::GaussianProcessRegressor [virtual]
computeCostsFromOutputs(const Vec &input, const Vec &output, const Vec &target, Vec &costs) const PLearn::GaussianProcessRegressor [virtual]
computeCostsOnly(const Vec &input, const Vec &target, Vec &costs) const PLearn::GaussianProcessRegressor [virtual]
PLearn::computeInputOutputConfMat(VMat inputs, real probability) const PLearn::PLearner
PLearn::PConditionalDistribution::computeInputOutputConfMat(VMat inputs, real probability) const PLearn::PLearner
PLearn::computeInputOutputMat(VMat inputs) const PLearn::PLearner
PLearn::PConditionalDistribution::computeInputOutputMat(VMat inputs) const PLearn::PLearner
computeOutput(const Vec &input, Vec &output) const PLearn::GaussianProcessRegressor [virtual]
computeOutput(const Vec &input, Vec &output) const PLearn::GaussianProcessRegressor [virtual]
computeOutputAndCosts(const Vec &input, const Vec &target, Vec &output, Vec &costs) const PLearn::GaussianProcessRegressor [virtual]
computeOutputAux(const Vec &input, Vec &output, Vec &kernel_evaluations) const PLearn::GaussianProcessRegressor [protected]
PLearn::computeOutputConfMat(VMat inputs, real probability) const PLearn::PLearner
PLearn::PConditionalDistribution::computeOutputConfMat(VMat inputs, real probability) const PLearn::PLearner
computeOutputCovMat(const Mat &inputs, Mat &outputs, TVec< Mat > &covariance_matrices) const PLearn::GaussianProcessRegressor [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]
PLearn::declareMethods(RemoteMethodMap &rmm)PLearn::PLearner [protected, static]
PLearn::PConditionalDistribution::declareMethods(RemoteMethodMap &rmm)PLearn::PDistribution [protected, static]
declareOptions(OptionList &ol)PLearn::GaussianProcessRegressor [protected, static]
declareOptions(OptionList &ol)PLearn::GaussianProcessRegressor [protected, static]
declaringFile()PLearn::GaussianProcessRegressor [inline, static]
declaringFile()PLearn::GaussianProcessRegressor [inline, static]
deepCopy(CopiesMap &copies) const PLearn::GaussianProcessRegressor [virtual]
deepCopy(CopiesMap &copies) const PLearn::GaussianProcessRegressor [virtual]
PLearn::deepCopyNoMap()PLearn::Object
PLearn::PConditionalDistribution::deepCopyNoMap()PLearn::Object
delta_curvePLearn::PDistribution [protected]
density(const Vec &y) const PLearn::PDistribution [virtual]
eigenvaluesPLearn::GaussianProcessRegressor
eigenvectorsPLearn::GaussianProcessRegressor
PLearn::expdirPLearn::PLearner
PLearn::PConditionalDistribution::expdirPLearn::PLearner
expectation() const PLearn::GaussianProcessRegressor [virtual]
expectation(Vec expected_y) const PLearn::GaussianProcessRegressor [virtual]
PLearn::PConditionalDistribution::expectation(Vec &mu) const PLearn::PDistribution [virtual]
finalize()PLearn::PLearner [virtual]
PLearn::finalizedPLearn::PLearner
PLearn::PConditionalDistribution::finalizedPLearn::PLearner
forget()PLearn::GaussianProcessRegressor [virtual]
forget()PLearn::GaussianProcessRegressor [virtual]
PLearn::forget_when_training_set_changesPLearn::PLearner [protected]
PLearn::PConditionalDistribution::forget_when_training_set_changesPLearn::PLearner [protected]
GaussianProcessRegressor()PLearn::GaussianProcessRegressor
GaussianProcessRegressor()PLearn::GaussianProcessRegressor
generate(Vec &y) const PLearn::PDistribution [virtual]
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]
PLearn::getExperimentDirectory() const PLearn::PLearner [inline]
PLearn::PConditionalDistribution::getExperimentDirectory() const PLearn::PLearner [inline]
getNPredicted() const PLearn::PDistribution [inline]
getNPredictor() const PLearn::PDistribution [inline]
PLearn::getOption(const string &optionname) const PLearn::Object
PLearn::PConditionalDistribution::getOption(const string &optionname) const PLearn::Object
getOptionList() const PLearn::GaussianProcessRegressor [virtual]
getOptionList() const PLearn::GaussianProcessRegressor [virtual]
getOptionMap() const PLearn::GaussianProcessRegressor [virtual]
getOptionMap() const PLearn::GaussianProcessRegressor [virtual]
getOptionsToRemoteTransmit() const PLearn::Object [virtual]
getOptionsToSave() const PLearn::Object [virtual]
getOutputNames() const PLearn::PLearner [virtual]
getRemoteMethodMap() const PLearn::GaussianProcessRegressor [virtual]
getRemoteMethodMap() const PLearn::GaussianProcessRegressor [virtual]
getTestCostIndex(const string &costname) const PLearn::GaussianProcessRegressor
getTestCostNames() const PLearn::GaussianProcessRegressor [virtual]
getTestCostNames() const PLearn::GaussianProcessRegressor [virtual]
getTrainCostIndex(const string &costname) const PLearn::GaussianProcessRegressor
getTrainCostNames() const PLearn::GaussianProcessRegressor [virtual]
getTrainCostNames() const PLearn::GaussianProcessRegressor [virtual]
PLearn::getTrainingSet() const PLearn::PLearner [inline]
PLearn::PConditionalDistribution::getTrainingSet() const PLearn::PLearner [inline]
PLearn::getTrainStatsCollector()PLearn::PLearner [inline]
PLearn::PConditionalDistribution::getTrainStatsCollector()PLearn::PLearner [inline]
PLearn::getValidationSet() const PLearn::PLearner [inline]
PLearn::PConditionalDistribution::getValidationSet() const PLearn::PLearner [inline]
Gram_matrix_normalizationPLearn::GaussianProcessRegressor
PLearn::hasOption(const string &optionname) const PLearn::Object
PLearn::PConditionalDistribution::hasOption(const string &optionname) const PLearn::Object
hyperOptimize(const Mat &inputs, const Mat &targets, VarArray &hyperparam_vars)PLearn::GaussianProcessRegressor [protected]
info() const PLearn::Object [virtual]
inherited typedefPLearn::GaussianProcessRegressor
inherited typedefPLearn::GaussianProcessRegressor [private]
PLearn::initTrain()PLearn::PLearner [protected]
PLearn::PConditionalDistribution::initTrain()PLearn::PLearner [protected]
input_part_sizePLearn::PConditionalDistribution
inputsize() const PLearn::PLearner [virtual]
PLearn::inputsize_PLearn::PLearner [protected]
PLearn::PConditionalDistribution::inputsize_PLearn::PLearner [protected]
inverseCovTimesVec(real sigma, Vec v, Vec Cinv_v) const PLearn::GaussianProcessRegressor [protected]
isStatefulLearner() const PLearn::PLearner [virtual]
KPLearn::GaussianProcessRegressor
kernelPLearn::GaussianProcessRegressor
KxxPLearn::GaussianProcessRegressor [mutable]
KxxiPLearn::GaussianProcessRegressor [mutable]
load(const PPath &filename)PLearn::Object [virtual]
log_density(const Vec &x) const PLearn::GaussianProcessRegressor [virtual]
lower_boundPLearn::PDistribution
m_active_set_indicesPLearn::GaussianProcessRegressor
m_algorithm_enumPLearn::GaussianProcessRegressor [protected]
m_alphaPLearn::GaussianProcessRegressor [protected]
m_ARD_hyperprefix_initvalPLearn::GaussianProcessRegressor
m_compute_confidencePLearn::GaussianProcessRegressor
m_confidence_epsilonPLearn::GaussianProcessRegressor
m_gram_inv_traintest_productPLearn::GaussianProcessRegressor [mutable, protected]
m_gram_inversePLearn::GaussianProcessRegressor [protected]
m_gram_inverse_productPLearn::GaussianProcessRegressor [mutable, protected]
m_gram_traintest_inputsPLearn::GaussianProcessRegressor [mutable, protected]
m_hyperparametersPLearn::GaussianProcessRegressor
m_include_biasPLearn::GaussianProcessRegressor
m_intervalsPLearn::GaussianProcessRegressor [mutable, protected]
m_kernelPLearn::GaussianProcessRegressor
m_kernel_evaluationsPLearn::GaussianProcessRegressor [mutable, protected]
m_optimizerPLearn::GaussianProcessRegressor
m_save_gram_matrixPLearn::GaussianProcessRegressor
m_sigma_reductorPLearn::GaussianProcessRegressor [mutable, protected]
m_solution_algorithmPLearn::GaussianProcessRegressor
m_subgram_inversePLearn::GaussianProcessRegressor [protected]
m_target_meanPLearn::GaussianProcessRegressor [protected]
m_training_inputsPLearn::GaussianProcessRegressor [protected]
m_weight_decayPLearn::GaussianProcessRegressor
makeDeepCopyFromShallowCopy(CopiesMap &copies)PLearn::GaussianProcessRegressor [virtual]
makeDeepCopyFromShallowCopy(CopiesMap &copies)PLearn::GaussianProcessRegressor [virtual]
PLearn::master_sends_testset_rowsPLearn::PLearner
PLearn::PConditionalDistribution::master_sends_testset_rowsPLearn::PLearner
max_nb_evectorsPLearn::GaussianProcessRegressor
mean_allKPLearn::GaussianProcessRegressor
meanKPLearn::GaussianProcessRegressor
missingExpectation(const Vec &input, Vec &mu)PLearn::PDistribution [virtual]
n_curve_pointsPLearn::PDistribution
PLearn::n_examplesPLearn::PLearner [protected]
PLearn::PConditionalDistribution::n_examplesPLearn::PLearner [protected]
n_outputsPLearn::GaussianProcessRegressor
n_predictedPLearn::PDistribution [mutable, protected]
n_predictorPLearn::PDistribution [mutable, protected]
PLearn::newread(PStream &in, unsigned int id=UINT_MAX)PLearn::Object
PLearn::PConditionalDistribution::newread(PStream &in, unsigned int id=UINT_MAX)PLearn::Object
newwrite(PStream &out) const PLearn::Object [virtual]
noise_sdPLearn::GaussianProcessRegressor
PLearn::nserversPLearn::PLearner
PLearn::PConditionalDistribution::nserversPLearn::PLearner
PLearn::nstagesPLearn::PLearner
PLearn::PConditionalDistribution::nstagesPLearn::PLearner
nTestCosts() const PLearn::GaussianProcessRegressor [inline, virtual]
nTrainCosts() const PLearn::GaussianProcessRegressor [inline, virtual]
PLearn::Object(bool call_build_=false)PLearn::Object
PLearn::PConditionalDistribution::Object(bool call_build_=false)PLearn::Object
oldread(istream &in)PLearn::Object [virtual]
outputs_defPLearn::PDistribution
outputsize() const PLearn::GaussianProcessRegressor [virtual]
outputsize() const PLearn::GaussianProcessRegressor [virtual]
PLearn::parallelize_herePLearn::PLearner
PLearn::PConditionalDistribution::parallelize_herePLearn::PLearner
PLearn::parseOptionName(const string &optionname, Object *&final_object, OptionList::iterator &option_iter, string &option_index)PLearn::Object
PLearn::parseOptionName(const string &optionname, const Object *&final_object, OptionList::iterator &option_iter, string &option_index) const PLearn::Object
PLearn::PConditionalDistribution::parseOptionName(const string &optionname, Object *&final_object, OptionList::iterator &option_iter, string &option_index)PLearn::Object
PLearn::PConditionalDistribution::parseOptionName(const string &optionname, const Object *&final_object, OptionList::iterator &option_iter, string &option_index) const PLearn::Object
PConditionalDistribution()PLearn::PConditionalDistribution
PDistribution()PLearn::PDistribution
PLearn::PLearner()PLearn::PLearner
PLearn::PConditionalDistribution::PLearner()PLearn::PLearner
PLearn::PPointable()PLearn::PPointable [inline]
PLearn::PPointable(const PPointable &other)PLearn::PPointable [inline]
PLearn::PConditionalDistribution::PPointable()PLearn::PPointable [inline]
PLearn::PConditionalDistribution::PPointable(const PPointable &other)PLearn::PPointable [inline]
predicted_partPLearn::PDistribution [mutable, protected]
predicted_sizePLearn::PDistribution [protected]
predictor_partPLearn::PDistribution [mutable, protected]
predictor_sizePLearn::PDistribution [protected]
PLearn::prepareToSendResults(PStream &out, int nres)PLearn::Object [static]
PLearn::PConditionalDistribution::prepareToSendResults(PStream &out, int nres)PLearn::Object [static]
processDataSet(VMat dataset) const PLearn::PLearner [virtual]
QFormInverse(real sigma2, Vec u) const PLearn::GaussianProcessRegressor [protected]
PLearn::random_genPLearn::PLearner [mutable, protected]
PLearn::PConditionalDistribution::random_genPLearn::PLearner [mutable, protected]
read(istream &in)PLearn::Object [virtual]
PLearn::readOptionVal(PStream &in, const string &optionname, unsigned int id=UINT_MAX)PLearn::Object
PLearn::PConditionalDistribution::readOptionVal(PStream &in, const string &optionname, unsigned int id=UINT_MAX)PLearn::Object
PLearn::ref() const PLearn::PPointable [inline]
PLearn::PConditionalDistribution::ref() const PLearn::PPointable [inline]
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]
PLearn::report_progressPLearn::PLearner
PLearn::PConditionalDistribution::report_progressPLearn::PLearner
resetGenerator(long g_seed)PLearn::PDistribution [virtual]
resetInternalState()PLearn::PLearner [virtual]
run()PLearn::Object [virtual]
save(const PPath &filename) const PLearn::Object [virtual]
PLearn::save_trainingset_prefixPLearn::PLearner
PLearn::PConditionalDistribution::save_trainingset_prefixPLearn::PLearner
PLearn::seed_PLearn::PLearner
PLearn::PConditionalDistribution::seed_PLearn::PLearner
setExperimentDirectory(const PPath &the_expdir)PLearn::PLearner [virtual]
setInput(const Vec &input) const PLearn::GaussianProcessRegressor [virtual]
PLearn::setOption(const string &optionname, const string &value)PLearn::Object
PLearn::PConditionalDistribution::setOption(const string &optionname, const string &value)PLearn::Object
setPredictor(const Vec &predictor, bool call_parent=true) const PLearn::PDistribution [virtual]
setPredictorPredictedSizes(int the_predictor_size, int the_predicted_size, bool call_parent=true)PLearn::PDistribution [virtual]
setTrainingSet(VMat training_set, bool call_forget=true)PLearn::GaussianProcessRegressor [virtual]
setTrainStatsCollector(PP< VecStatsCollector > statscol)PLearn::PLearner [virtual]
setValidationSet(VMat validset)PLearn::PLearner [virtual]
splitCond(const Vec &input) const PLearn::PDistribution [protected]
PLearn::stagePLearn::PLearner
PLearn::PConditionalDistribution::stagePLearn::PLearner
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]
survival_fn(const Vec &y) const PLearn::PDistribution [virtual]
targetsize() const PLearn::PLearner [virtual]
PLearn::targetsize_PLearn::PLearner [protected]
PLearn::PConditionalDistribution::targetsize_PLearn::PLearner [protected]
test(VMat testset, PP< VecStatsCollector > test_stats, VMat testoutputs=0, VMat testcosts=0) const PLearn::PLearner [virtual]
PLearn::test_minibatch_sizePLearn::PLearner
PLearn::PConditionalDistribution::test_minibatch_sizePLearn::PLearner
train()PLearn::GaussianProcessRegressor [virtual]
train()PLearn::GaussianProcessRegressor [virtual]
PLearn::train_setPLearn::PLearner [protected]
PLearn::PConditionalDistribution::train_setPLearn::PLearner [protected]
PLearn::train_statsPLearn::PLearner [protected]
PLearn::PConditionalDistribution::train_statsPLearn::PLearner [protected]
trainProjectedProcess(const Mat &all_training_inputs, const Mat &sub_training_inputs, const Mat &all_training_targets)PLearn::GaussianProcessRegressor [protected]
unknownOutput(char def, const Vec &input, Vec &output, int &k) const PLearn::PDistribution [protected, virtual]
PLearn::unref() const PLearn::PPointable [inline]
PLearn::PConditionalDistribution::unref() const PLearn::PPointable [inline]
upper_boundPLearn::PDistribution
PLearn::usage() const PLearn::PPointable [inline]
PLearn::PConditionalDistribution::usage() const PLearn::PPointable [inline]
use(VMat testset, VMat outputs) const PLearn::PLearner [virtual]
PLearn::use_a_separate_random_generator_for_testingPLearn::PLearner
PLearn::PConditionalDistribution::use_a_separate_random_generator_for_testingPLearn::PLearner
useOnTrain(Mat &outputs) const PLearn::PLearner [virtual]
PLearn::validation_setPLearn::PLearner [protected]
PLearn::PConditionalDistribution::validation_setPLearn::PLearner [protected]
variance() const PLearn::GaussianProcessRegressor [virtual]
variance(Vec diag_variances) const PLearn::GaussianProcessRegressor [virtual]
PLearn::PConditionalDistribution::variance(Mat &cov) const PLearn::PDistribution [virtual]
PLearn::verbosityPLearn::PLearner
PLearn::PConditionalDistribution::verbosityPLearn::PLearner
weightsize() const PLearn::PLearner [virtual]
PLearn::weightsize_PLearn::PLearner [protected]
PLearn::PConditionalDistribution::weightsize_PLearn::PLearner [protected]
write(ostream &out) const PLearn::Object [virtual]
PLearn::writeOptionVal(PStream &out, const string &optionname) const PLearn::Object
PLearn::PConditionalDistribution::writeOptionVal(PStream &out, const string &optionname) const PLearn::Object
~GaussianProcessRegressor()PLearn::GaussianProcessRegressor [virtual]
~Object()PLearn::Object [virtual]
~PPointable()PLearn::PPointable [inline, virtual]
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