PLearn 0.1
PLearn::GaussianDBNRegression Member List
This is the complete list of members for PLearn::GaussianDBNRegression, including all inherited members.
_classname_()PLearn::GaussianDBNRegression [static]
_getOptionList_()PLearn::GaussianDBNRegression [static]
_getRemoteMethodMap_()PLearn::GaussianDBNRegression [static]
_isa_(const Object *o)PLearn::GaussianDBNRegression [static]
_new_instance_for_typemap_()PLearn::GaussianDBNRegression [static]
_static_initialize_()PLearn::GaussianDBNRegression [static]
_static_initializer_PLearn::GaussianDBNRegression [static]
activation_gradientsPLearn::GaussianDBNRegression [mutable, protected]
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::GaussianDBNRegression [virtual]
build_()PLearn::GaussianDBNRegression [private]
build_from_train_set()PLearn::PLearner [inline, protected, virtual]
build_layers()PLearn::GaussianDBNRegression [private]
build_params()PLearn::GaussianDBNRegression [private]
call(const string &methodname, int nargs, PStream &io)PLearn::Object [virtual]
cdf(const Vec &y) const PLearn::GaussianDBNRegression [virtual]
changeOption(const string &optionname, const string &value)PLearn::Object
changeOptions(const map< string, string > &name_value)PLearn::Object [virtual]
classname() const PLearn::GaussianDBNRegression [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::GaussianDBNRegression [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::PDistribution [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]
declareMethods(RemoteMethodMap &rmm)PLearn::PDistribution [protected, static]
declareOptions(OptionList &ol)PLearn::GaussianDBNRegression [protected, static]
declaringFile()PLearn::GaussianDBNRegression [inline, static]
deepCopy(CopiesMap &copies) const PLearn::GaussianDBNRegression [virtual]
deepCopyNoMap()PLearn::Object
delta_curvePLearn::PDistribution [protected]
density(const Vec &y) const PLearn::GaussianDBNRegression [virtual]
expdirPLearn::PLearner
expectation(Vec &mu) const PLearn::GaussianDBNRegression [virtual]
expectation_gradientsPLearn::GaussianDBNRegression [mutable, protected]
finalize()PLearn::PLearner [virtual]
finalizedPLearn::PLearner
fine_tuning_methodPLearn::GaussianDBNRegression
fineTuneByGradientDescent(const Vec &input)PLearn::GaussianDBNRegression [protected, virtual]
fineTuneByGradientDescentLastLayer(const Vec &input)PLearn::GaussianDBNRegression [protected]
forget()PLearn::GaussianDBNRegression [virtual]
forget_when_training_set_changesPLearn::PLearner [protected]
GaussianDBNRegression()PLearn::GaussianDBNRegression
generate(Vec &y) const PLearn::GaussianDBNRegression [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]
getExperimentDirectory() const PLearn::PLearner [inline]
getNPredicted() const PLearn::PDistribution [inline]
getNPredictor() const PLearn::PDistribution [inline]
getOption(const string &optionname) const PLearn::Object
getOptionList() const PLearn::GaussianDBNRegression [virtual]
getOptionMap() const PLearn::GaussianDBNRegression [virtual]
getOptionsToRemoteTransmit() const PLearn::Object [virtual]
getOptionsToSave() const PLearn::Object [virtual]
getOutputNames() const PLearn::PLearner [virtual]
getRemoteMethodMap() const PLearn::GaussianDBNRegression [virtual]
getTestCostIndex(const string &costname) const PLearn::PLearner
getTestCostNames() const PLearn::GaussianDBNRegression [virtual]
getTrainCostIndex(const string &costname) const PLearn::PLearner
getTrainCostNames() const PLearn::PDistribution [virtual]
getTrainingSet() const PLearn::PLearner [inline]
getTrainStatsCollector()PLearn::PLearner [inline]
getValidationSet() const PLearn::PLearner [inline]
greedyStep(const Vec &predictor, int params_index)PLearn::GaussianDBNRegression [protected, virtual]
hasOption(const string &optionname) const PLearn::Object
info() const PLearn::Object [virtual]
inherited typedefPLearn::GaussianDBNRegression [private]
initialization_methodPLearn::GaussianDBNRegression
initTrain()PLearn::PLearner [protected]
input_paramsPLearn::GaussianDBNRegression
inputsize() const PLearn::PLearner [virtual]
inputsize_PLearn::PLearner [protected]
isStatefulLearner() const PLearn::PLearner [virtual]
last_layerPLearn::GaussianDBNRegression
layersPLearn::GaussianDBNRegression
learning_ratePLearn::GaussianDBNRegression
load(const PPath &filename)PLearn::Object [virtual]
log_density(const Vec &y) const PLearn::GaussianDBNRegression [virtual]
lower_boundPLearn::PDistribution
makeDeepCopyFromShallowCopy(CopiesMap &copies)PLearn::GaussianDBNRegression [virtual]
master_sends_testset_rowsPLearn::PLearner
missingExpectation(const Vec &input, Vec &mu)PLearn::PDistribution [virtual]
n_curve_pointsPLearn::PDistribution
n_examplesPLearn::PLearner [protected]
n_layersPLearn::GaussianDBNRegression
n_predictedPLearn::PDistribution [mutable, protected]
n_predictorPLearn::PDistribution [mutable, protected]
newread(PStream &in, unsigned int id=UINT_MAX)PLearn::Object
newwrite(PStream &out) const PLearn::Object [virtual]
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]
output_gradientPLearn::GaussianDBNRegression [mutable, protected]
outputs_defPLearn::PDistribution
outputsize() const PLearn::PDistribution [virtual]
parallelize_herePLearn::PLearner
paramsPLearn::GaussianDBNRegression
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
PPointable()PLearn::PPointable [inline]
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]
prepareToSendResults(PStream &out, int nres)PLearn::Object [static]
processDataSet(VMat dataset) const PLearn::PLearner [virtual]
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]
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]
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]
save_trainingset_prefixPLearn::PLearner
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::GaussianDBNRegression [virtual]
setPredictorPredictedSizes(int the_predictor_size, int the_predicted_size, bool call_parent=true)PLearn::GaussianDBNRegression [virtual]
setTrainingSet(VMat training_set, bool call_forget=true)PLearn::PLearner [virtual]
setTrainStatsCollector(PP< VecStatsCollector > statscol)PLearn::PLearner [virtual]
setValidationSet(VMat validset)PLearn::PLearner [virtual]
splitCond(const Vec &input) const PLearn::PDistribution [protected]
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::GaussianDBNRegression [virtual]
target_layerPLearn::GaussianDBNRegression
target_paramsPLearn::GaussianDBNRegression
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_minibatch_sizePLearn::PLearner
train()PLearn::GaussianDBNRegression [virtual]
train_setPLearn::PLearner [protected]
train_statsPLearn::PLearner [protected]
training_schedulePLearn::GaussianDBNRegression
unknownOutput(char def, const Vec &input, Vec &output, int &k) const PLearn::PDistribution [protected, virtual]
unref() const PLearn::PPointable [inline]
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_sample_rather_than_expectation_in_positive_phase_statisticsPLearn::GaussianDBNRegression
useOnTrain(Mat &outputs) const PLearn::PLearner [virtual]
validation_setPLearn::PLearner [protected]
variance(Mat &cov) const PLearn::GaussianDBNRegression [virtual]
verbosityPLearn::PLearner
weight_decayPLearn::GaussianDBNRegression
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
~Object()PLearn::Object [virtual]
~PPointable()PLearn::PPointable [inline, virtual]
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