PLearn 0.1
PLearn::TransformationLearner Member List
This is the complete list of members for PLearn::TransformationLearner, including all inherited members.
_classname_()PLearn::TransformationLearner [static]
_getOptionList_()PLearn::TransformationLearner [static]
_getRemoteMethodMap_()PLearn::TransformationLearner [static]
_isa_(const Object *o)PLearn::TransformationLearner [static]
_new_instance_for_typemap_()PLearn::TransformationLearner [static]
_static_initialize_()PLearn::TransformationLearner [static]
_static_initializer_PLearn::TransformationLearner [static]
applyTransformationOn(int transformIdx, const Vec &src, Vec &dst) const PLearn::TransformationLearner [inline, private]
asString() const PLearn::Object [virtual]
asStringRemoteTransmit() const PLearn::Object [virtual]
BPLearn::TransformationLearner [protected]
B_CPLearn::TransformationLearner [protected]
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]
batchGeneratePredictedFrom(const Vec &center, Mat &samples) const PLearn::TransformationLearner
batchGeneratePredictedFrom(const Vec &center, Mat &samples, int transformIdx) const PLearn::TransformationLearner
behaviorPLearn::TransformationLearner
biasOffsetPLearn::TransformationLearner
biasPeriodPLearn::TransformationLearner
biasSetPLearn::TransformationLearner [protected]
build()PLearn::TransformationLearner [virtual]
build_()PLearn::TransformationLearner [private]
build_from_train_set()PLearn::PLearner [inline, protected, virtual]
buildLearnedParameters()PLearn::TransformationLearner
CPLearn::TransformationLearner [protected]
call(const string &methodname, int nargs, PStream &io)PLearn::Object [virtual]
cdf(const Vec &y) const PLearn::PDistribution [virtual]
changeOption(const string &optionname, const string &value)PLearn::Object
changeOptions(const map< string, string > &name_value)PLearn::Object [virtual]
classname() const PLearn::TransformationLearner [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::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
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]
computeReconstructionWeight(const ReconstructionCandidate &gc) const PLearn::TransformationLearner [inline, private]
computeReconstructionWeight(int targetIdx, int neighborIdx, int transformIdx) const PLearn::TransformationLearner [inline, private]
computeReconstructionWeight(const Vec &target, int neighborIdx, int transformIdx) const PLearn::TransformationLearner [inline, private]
computeReconstructionWeight(const Vec &target, const Vec &neighbor, int transformIdx) const PLearn::TransformationLearner [inline, private]
computeReconstructionWeight(const Vec &target, const Vec &neighbor, int transformIdx, Vec &predictedTarget) const PLearn::TransformationLearner [inline, private]
declareMethods(RemoteMethodMap &rmm)PLearn::TransformationLearner [protected, static]
declareOptions(OptionList &ol)PLearn::TransformationLearner [protected, static]
declaringFile()PLearn::TransformationLearner [inline, static]
deepCopy(CopiesMap &copies) const PLearn::TransformationLearner [virtual]
deepCopyNoMap()PLearn::Object
delta_curvePLearn::PDistribution [protected]
density(const Vec &y) const PLearn::PDistribution [virtual]
dirichlet_sample(real alpha, Vec &sample) const PLearn::TransformationLearner [private]
DIV_weights(real numWeight, real denomWeight) const PLearn::TransformationLearner [inline, private]
diversityFactorPLearn::TransformationLearner
emphasisOnDiversityPLearn::TransformationLearner
EStep()PLearn::TransformationLearner [private]
expandTargetNeighborPairInReconstructionSet(int targetIdx, int neighborIdx, int candidateStartIdx)PLearn::TransformationLearner [private]
expdirPLearn::PLearner
expectation(Vec &mu) const PLearn::PDistribution [virtual]
fbtrc_neighborPLearn::TransformationLearner [mutable, protected]
fbtrc_predictedTargetPLearn::TransformationLearner [mutable, protected]
fbtrc_targetPLearn::TransformationLearner [mutable, protected]
fbwn_neighborPLearn::TransformationLearner [mutable, protected]
fbwn_predictedTargetPLearn::TransformationLearner [mutable, protected]
fbwn_targetPLearn::TransformationLearner [mutable, protected]
finalize()PLearn::PLearner [virtual]
finalizedPLearn::PLearner
findBestTargetReconstructionCandidates(int targetIdx, priority_queue< ReconstructionCandidate > &pq)PLearn::TransformationLearner [private]
findBestWeightedNeighbors(int targetIdx, int transformIdx, priority_queue< ReconstructionCandidate > &pq)PLearn::TransformationLearner [private]
findNearestNeighbors(int targetIdx, priority_queue< pair< real, int > > &pq)PLearn::TransformationLearner [private]
fnn_neighborPLearn::TransformationLearner [mutable, protected]
fnn_targetPLearn::TransformationLearner [mutable, protected]
forget()PLearn::TransformationLearner [virtual]
forget_when_training_set_changesPLearn::PLearner [protected]
gamma_sample(real alpha, real beta=1) const PLearn::TransformationLearner [private]
generate(Vec &y) const PLearn::TransformationLearner [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]
generatePredictedFrom(const Vec &source, Vec &sample) const PLearn::TransformationLearner
generatePredictedFrom(const Vec &source, Vec &sample, int transformIdx) const PLearn::TransformationLearner
generatePredictor(Vec &x)PLearn::PDistribution [virtual]
generatePredictorGivenPredicted(Vec &x, const Vec &y)PLearn::PDistribution [virtual]
generatorBuild(int inputSpaceDim_=2, TVec< Mat > transforms_=TVec< Mat >(), Mat biasSet_=Mat(), real noiseVariance_=-1.0, Vec transformDistribution_=Vec())PLearn::TransformationLearner
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::TransformationLearner [virtual]
getOptionMap() const PLearn::TransformationLearner [virtual]
getOptionsToRemoteTransmit() const PLearn::Object [virtual]
getOptionsToSave() const PLearn::Object [virtual]
getOutputNames() const PLearn::PLearner [virtual]
getRemoteMethodMap() const PLearn::TransformationLearner [virtual]
getTestCostIndex(const string &costname) const PLearn::PLearner
getTestCostNames() const PLearn::PDistribution [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]
hasOption(const string &optionname) const PLearn::Object
info() const PLearn::Object [virtual]
inherited typedefPLearn::TransformationLearner [private]
INIT_weight(real initValue) const PLearn::TransformationLearner [inline, private]
initEStep()PLearn::TransformationLearner [private]
initEStepA()PLearn::TransformationLearner [private]
initEStepB()PLearn::TransformationLearner [private]
initializationModePLearn::TransformationLearner
initNoiseVariance()PLearn::TransformationLearner
initTrain()PLearn::PLearner [protected]
initTransformDistribution()PLearn::TransformationLearner
initTransformsParameters()PLearn::TransformationLearner
inputsize() const PLearn::TransformationLearner [virtual]
inputsize_PLearn::PLearner [protected]
inputSpaceDimPLearn::TransformationLearner [protected]
isStatefulLearner() const PLearn::PLearner [virtual]
isWellDefined(Vec &distribution) const PLearn::TransformationLearner [private]
largeEStepA()PLearn::TransformationLearner [private]
largeEStepAOffsetPLearn::TransformationLearner
largeEStepAPeriodPLearn::TransformationLearner
largeEStepB()PLearn::TransformationLearner [private]
largeEStepBOffsetPLearn::TransformationLearner
largeEStepBPeriodPLearn::TransformationLearner
learnNoiseVariancePLearn::TransformationLearner
learnTransformDistributionPLearn::TransformationLearner
lg_neighborPLearn::TransformationLearner [mutable, protected]
lg_predictedTargetPLearn::TransformationLearner [mutable, protected]
load(const PPath &filename)PLearn::Object [virtual]
log_density(const Vec &y) const PLearn::TransformationLearner [virtual]
lower_boundPLearn::PDistribution
mainLearnerBuild()PLearn::TransformationLearner
makeDeepCopyFromShallowCopy(CopiesMap &copies)PLearn::TransformationLearner [virtual]
master_sends_testset_rowsPLearn::PLearner
minimumProbaPLearn::TransformationLearner
missingExpectation(const Vec &input, Vec &mu)PLearn::PDistribution [virtual]
msb_neighborPLearn::TransformationLearner [mutable, protected]
msb_newBiasSetPLearn::TransformationLearner [mutable, protected]
msb_normsPLearn::TransformationLearner [mutable, protected]
msb_reconstructionPLearn::TransformationLearner [mutable, protected]
msb_targetPLearn::TransformationLearner [mutable, protected]
msnvMAP_neighborPLearn::TransformationLearner [mutable, protected]
msnvMAP_reconstructionPLearn::TransformationLearner [mutable, protected]
msnvMAP_targetPLearn::TransformationLearner [mutable, protected]
msnvMAP_total_kPLearn::TransformationLearner [mutable, protected]
mst_neighborPLearn::TransformationLearner [mutable, protected]
mst_pivotsPLearn::TransformationLearner [mutable, protected]
mst_targetPLearn::TransformationLearner [mutable, protected]
mst_vPLearn::TransformationLearner [mutable, protected]
mstd_BPLearn::TransformationLearner [mutable, protected]
mstd_CPLearn::TransformationLearner [mutable, protected]
mstd_DPLearn::TransformationLearner [mutable, protected]
mstd_neighborPLearn::TransformationLearner [mutable, protected]
mstd_pivotsPLearn::TransformationLearner [mutable, protected]
mstd_targetPLearn::TransformationLearner [mutable, protected]
mstd_vPLearn::TransformationLearner [mutable, protected]
MStep()PLearn::TransformationLearner [private]
MStepBias()PLearn::TransformationLearner [private]
MStepNoiseVariance()PLearn::TransformationLearner [private]
MStepNoiseVarianceMAP(real alpha, real beta)PLearn::TransformationLearner [private]
MStepTransformationDiv(int transformIdx)PLearn::TransformationLearner [private]
MStepTransformations()PLearn::TransformationLearner [private]
MStepTransformDistribution()PLearn::TransformationLearner [private]
MStepTransformDistributionMAP(real alpha)PLearn::TransformationLearner [private]
MULT_INVERSE_weight(real weight) const PLearn::TransformationLearner [inline, private]
MULT_weights(real weight1, real weight2) const PLearn::TransformationLearner [inline, private]
n_curve_pointsPLearn::PDistribution
n_examplesPLearn::PLearner [protected]
n_predictedPLearn::PDistribution [mutable, protected]
n_predictorPLearn::PDistribution [mutable, protected]
nbNeighborsPLearn::TransformationLearner
nbReconstructionsPLearn::TransformationLearner [protected]
nbTargetReconstructionsPLearn::TransformationLearner [protected]
nbTransformsPLearn::TransformationLearner
newDistributionPLearn::TransformationLearner [mutable, protected]
newread(PStream &in, unsigned int id=UINT_MAX)PLearn::Object
newwrite(PStream &out) const PLearn::Object [virtual]
nextStage()PLearn::TransformationLearner [private]
noiseAlphaPLearn::TransformationLearner
noiseBetaPLearn::TransformationLearner
noiseVariancePLearn::TransformationLearner
noiseVarianceOffsetPLearn::TransformationLearner
noiseVariancePeriodPLearn::TransformationLearner
normalizeTargetWeights(int targetIdx, real totalWeight)PLearn::TransformationLearner [inline, private]
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]
outputs_defPLearn::PDistribution
outputsize() const PLearn::PDistribution [virtual]
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
pickNeighborIdx() const PLearn::TransformationLearner
pickTransformIdx() const PLearn::TransformationLearner
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]
PROBA_weight(real weight) const PLearn::TransformationLearner [inline, private]
processDataSet(VMat dataset) const PLearn::PLearner [virtual]
random_genPLearn::PLearner [mutable, protected]
randomWeight() const PLearn::TransformationLearner [inline, private]
read(istream &in)PLearn::Object [virtual]
readOptionVal(PStream &in, const string &optionname, unsigned int id=UINT_MAX)PLearn::Object
reconstructionEuclideanDistance(int candidateIdx)PLearn::TransformationLearner [inline, private]
reconstructionEuclideanDistance(const Vec &target, const Vec &neighbor, int transformIdx, Vec &reconstruction) const PLearn::TransformationLearner [inline, private]
reconstructionSetPLearn::TransformationLearner [protected]
ref() const PLearn::PPointable [inline]
regOnNoiseVariancePLearn::TransformationLearner
regOnTransformDistributionPLearn::TransformationLearner
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]
return_dirichlet_sample(real alpha) const PLearn::TransformationLearner [private]
returnAllTransforms() const PLearn::TransformationLearner
returnGeneratedSamplesFrom(Vec center, int n, int transformIdx=-1) const PLearn::TransformationLearner
returnNeighbors(int targetIdx) const PLearn::TransformationLearner
returnPredictedFrom(Vec source, int transformIdx=-1) const PLearn::TransformationLearner
returnReconstructionCandidates(int targetIdx) const PLearn::TransformationLearner
returnReconstructions(int targetIdx) const PLearn::TransformationLearner
returnSequenceDataSet(Vec start, int n, int transformIdx=-1) const PLearn::TransformationLearner
returnTrainingPoint(int idx) const PLearn::TransformationLearner
returnTransform(int transformIdx) const PLearn::TransformationLearner
returnTreeDataSet(Vec root, int deepness, int branchingFactor, int transformIdx=-1) const PLearn::TransformationLearner
run()PLearn::Object [virtual]
save(const PPath &filename) const PLearn::Object [virtual]
save_trainingset_prefixPLearn::PLearner
seed_PLearn::PLearner
seeTargetReconstructionSet(int targetIdx, TVec< ReconstructionCandidate > &targetReconstructionSet) const PLearn::TransformationLearner [private]
seeTrainingPoint(const int idx, Vec &dst) const PLearn::TransformationLearner [inline, private]
sequenceDataSet(const Vec &start, int n, Mat &dataPoints, int transformIdx=-1) const PLearn::TransformationLearner
ses_neighborPLearn::TransformationLearner [mutable, protected]
ses_predictedTargetPLearn::TransformationLearner [mutable, protected]
ses_targetPLearn::TransformationLearner [mutable, protected]
setExperimentDirectory(const PPath &the_expdir)PLearn::PLearner [virtual]
setNoiseVariance(real nv)PLearn::TransformationLearner
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::PLearner [virtual]
setTrainStatsCollector(PP< VecStatsCollector > statscol)PLearn::PLearner [virtual]
setTransformDistribution(Vec td)PLearn::TransformationLearner
setTransformsParameters(TVec< Mat > transforms, Mat bias=Mat())PLearn::TransformationLearner
setValidationSet(VMat validset)PLearn::PLearner [virtual]
smallEStep()PLearn::TransformationLearner [private]
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]
stp_vPLearn::TransformationLearner [mutable, protected]
stp_wPLearn::TransformationLearner [mutable, protected]
sub_test(VMat testset, PP< VecStatsCollector > test_stats, bool rtestoutputs, bool rtestcosts) const PLearn::PLearner [virtual]
SUM_weights(real weight1, real weight2) const PLearn::TransformationLearner [inline, private]
survival_fn(const Vec &y) const PLearn::PDistribution [virtual]
targetReconstructionSetPLearn::TransformationLearner [protected]
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::TransformationLearner [virtual]
train_setPLearn::PLearner [protected]
train_statsPLearn::PLearner [protected]
trainingSetLengthPLearn::TransformationLearner [protected]
TransformationLearner()PLearn::TransformationLearner
transformDistributionPLearn::TransformationLearner
transformDistributionAlphaPLearn::TransformationLearner
transformDistributionOffsetPLearn::TransformationLearner
transformDistributionPeriodPLearn::TransformationLearner
transformFamilyPLearn::TransformationLearner
transformsPLearn::TransformationLearner [protected]
transformsOffsetPLearn::TransformationLearner
transformsPeriodPLearn::TransformationLearner
transformsSDPLearn::TransformationLearner [protected]
transformsSetPLearn::TransformationLearner [protected]
transformsVariancePLearn::TransformationLearner
treeDataSet(const Vec &root, int deepness, int branchingFactor, Mat &dataPoints, int transformIdx=-1) const PLearn::TransformationLearner
unknownOutput(char def, const Vec &input, Vec &output, int &k) const PLearn::PDistribution [protected, virtual]
unref() const PLearn::PPointable [inline]
updateReconstructionWeight(int candidateIdx)PLearn::TransformationLearner [inline, private]
updateReconstructionWeight(int candidateIdx, const Vec &target, const Vec &neighbor, int transformIdx, Vec &predictedTarget)PLearn::TransformationLearner [inline, private]
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
useOnTrain(Mat &outputs) const PLearn::PLearner [virtual]
validation_setPLearn::PLearner [protected]
variance(Mat &cov) const PLearn::PDistribution [virtual]
verbosityPLearn::PLearner
weightsize() const PLearn::PLearner [virtual]
weightsize_PLearn::PLearner [protected]
withBiasPLearn::TransformationLearner
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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