PLearn 0.1
PLearn::AddLayersNNet Member List
This is the complete list of members for PLearn::AddLayersNNet, including all inherited members.
_classname_()PLearn::AddLayersNNet [static]
_getOptionList_()PLearn::AddLayersNNet [static]
_getRemoteMethodMap_()PLearn::AddLayersNNet [static]
_isa_(const Object *o)PLearn::AddLayersNNet [static]
_new_instance_for_typemap_()PLearn::AddLayersNNet [static]
_static_initialize_()PLearn::AddLayersNNet [static]
_static_initializer_PLearn::AddLayersNNet [static]
add_hiddenPLearn::AddLayersNNet
added_hidden_transfer_funcPLearn::AddLayersNNet
AddLayersNNet()PLearn::AddLayersNNet
alpha_adaboostPLearn::NNet [protected]
applyTransferFunc(const Var &before_transfer_func, Var &output)PLearn::NNet [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]
bag_inputsPLearn::NNet [protected]
bag_sizePLearn::NNet [protected]
batch_sizePLearn::NNet
batchComputeOutputAndConfidence(VMat inputs, real probability, VMat outputs_and_confidence) const PLearn::PLearner [virtual]
bias_decayPLearn::NNet
build()PLearn::AddLayersNNet [virtual]
build_()PLearn::AddLayersNNet [private]
build_from_train_set()PLearn::PLearner [inline, protected, virtual]
buildBagOutputFromBagInputs(const Var &input, Var &before_transfer_func, const Var &bag_inputs, const Var &bag_size, Var &bag_output)PLearn::NNet [protected]
buildCosts(const Var &output, const Var &target, const Var &hidden_layer, const Var &before_transfer_func)PLearn::NNet [protected]
buildFuncs(const Var &the_input, const Var &the_output, const Var &the_target, const Var &the_sampleweight, const Var &the_bag_size)PLearn::NNet [protected]
buildOutputFromInput(const Var &the_input, Var &hidden_layer, Var &before_transfer_func)PLearn::NNet [protected]
buildPenalties(const Var &hidden_layer)PLearn::AddLayersNNet [protected, virtual]
buildTargetAndWeight()PLearn::NNet [protected]
call(const string &methodname, int nargs, PStream &io)PLearn::Object [virtual]
changeOption(const string &optionname, const string &value)PLearn::Object
changeOptions(const map< string, string > &name_value)PLearn::Object [virtual]
classification_regularizerPLearn::NNet
classname() const PLearn::AddLayersNNet [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::NNet [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::NNet [virtual]
computeOutputAndCosts(const Vec &input, const Vec &target, Vec &output, Vec &costs) const PLearn::NNet [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]
cost_funcsPLearn::NNet
costsPLearn::NNet [protected]
declareMethods(RemoteMethodMap &rmm)PLearn::PLearner [protected, static]
declareOptions(OptionList &ol)PLearn::AddLayersNNet [protected, static]
declaringFile()PLearn::AddLayersNNet [inline, static]
deepCopy(CopiesMap &copies) const PLearn::AddLayersNNet [virtual]
deepCopyNoMap()PLearn::Object
direct_in_to_outPLearn::NNet
direct_in_to_out_weight_decayPLearn::NNet
do_not_change_paramsPLearn::NNet
expdirPLearn::PLearner
fillWeights(const Var &weights, bool clear_first_row)PLearn::NNet [protected]
finalize()PLearn::PLearner [virtual]
finalizedPLearn::PLearner
first_class_is_junkPLearn::NNet
first_hidden_layerPLearn::NNet
first_hidden_layer_is_outputPLearn::NNet
fixed_output_weightsPLearn::NNet
forget()PLearn::NNet [virtual]
forget_when_training_set_changesPLearn::PLearner [protected]
getCost(const string &costname, const Var &output, const Var &target, const Var &before_transfer_func)PLearn::NNet [protected, virtual]
getExperimentDirectory() const PLearn::PLearner [inline]
getHiddenUnitsActivation(int layer)PLearn::AddLayersNNet
getHiddenWeights(int layer)PLearn::AddLayersNNet
getOption(const string &optionname) const PLearn::Object
getOptionList() const PLearn::AddLayersNNet [virtual]
getOptionMap() const PLearn::AddLayersNNet [virtual]
getOptionsToRemoteTransmit() const PLearn::Object [virtual]
getOptionsToSave() const PLearn::Object [virtual]
getOutputHiddenWeights(int layer)PLearn::AddLayersNNet
getOutputNames() const PLearn::PLearner [virtual]
getRemoteMethodMap() const PLearn::AddLayersNNet [virtual]
getTestCostIndex(const string &costname) const PLearn::PLearner
getTestCostNames() const PLearn::NNet [virtual]
getTrainCostIndex(const string &costname) const PLearn::PLearner
getTrainCostNames() const PLearn::NNet [virtual]
getTrainingSet() const PLearn::PLearner [inline]
getTrainStatsCollector()PLearn::PLearner [inline]
getValidationSet() const PLearn::PLearner [inline]
getW1()PLearn::NNet [inline, virtual]
getW2()PLearn::NNet [inline, virtual]
getWdirect()PLearn::NNet [inline, virtual]
getWout()PLearn::NNet [inline, virtual]
hasOption(const string &optionname) const PLearn::Object
hidden_layerPLearn::NNet
hidden_layersPLearn::AddLayersNNet [protected]
hidden_transfer_funcPLearn::NNet
hidden_weightsPLearn::AddLayersNNet [protected]
hiddenLayer(const Var &input, const Var &weights, string transfer_func="default", VarArray *ratio_quad_weights=NULL)PLearn::NNet [protected]
info() const PLearn::Object [virtual]
inherited typedefPLearn::AddLayersNNet [private]
initialization_methodPLearn::NNet
initializeParams(bool set_seed=true)PLearn::AddLayersNNet [protected, virtual]
initTrain()PLearn::PLearner [protected]
inputPLearn::NNet
input_reconstruction_penaltyPLearn::NNet
input_to_outputPLearn::NNet [mutable]
inputsize() const PLearn::PLearner [virtual]
inputsize_PLearn::PLearner [protected]
interval_maxvalPLearn::NNet
interval_minvalPLearn::NNet
invarsPLearn::NNet [protected]
isStatefulLearner() const PLearn::PLearner [virtual]
junk_probPLearn::NNet [protected]
L1_penaltyPLearn::NNet
layer1_bias_decayPLearn::NNet
layer1_weight_decayPLearn::NNet
layer2_bias_decayPLearn::NNet
layer2_weight_decayPLearn::NNet
load(const PPath &filename)PLearn::Object [virtual]
makeDeepCopyFromShallowCopy(CopiesMap &copies)PLearn::AddLayersNNet [virtual]
marginPLearn::NNet
master_sends_testset_rowsPLearn::PLearner
max_bag_sizePLearn::NNet
n_examplesPLearn::PLearner [protected]
n_non_params_in_first_hidden_layerPLearn::NNet
n_training_bagsPLearn::NNet [protected]
newread(PStream &in, unsigned int id=UINT_MAX)PLearn::Object
newwrite(PStream &out) const PLearn::Object [virtual]
nhiddenPLearn::NNet
nhidden2PLearn::NNet
NNet()PLearn::NNet
noutputsPLearn::NNet
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]
operate_on_bagsPLearn::NNet
optimizerPLearn::NNet
outbiasPLearn::NNet
outputPLearn::NNet [protected]
output_and_target_to_costPLearn::NNet [mutable]
output_layer_bias_decayPLearn::NNet
output_layer_weight_decayPLearn::NNet
output_transfer_funcPLearn::NNet
outputsize() const PLearn::NNet [virtual]
parallelize_herePLearn::PLearner
paramsPLearn::NNet [protected]
paramsvaluesPLearn::NNet
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
parts_sizePLearn::AddLayersNNet
penaltiesPLearn::NNet [protected]
penalty_typePLearn::NNet
PLearner()PLearn::PLearner
PPointable()PLearn::PPointable [inline]
PPointable(const PPointable &other)PLearn::PPointable [inline]
predicted_inputPLearn::NNet [protected]
prepareToSendResults(PStream &out, int nres)PLearn::Object [static]
processDataSet(VMat dataset) const PLearn::PLearner [virtual]
random_genPLearn::PLearner [mutable, protected]
ratio_rankPLearn::NNet
rbf_centersPLearn::NNet [protected]
rbf_layer_sizePLearn::NNet
rbf_sigmasPLearn::NNet [protected]
read(istream &in)PLearn::Object [virtual]
readOptionVal(PStream &in, const string &optionname, unsigned int id=UINT_MAX)PLearn::Object
real_parts_sizePLearn::AddLayersNNet [protected]
ref() const PLearn::PPointable [inline]
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
resetInternalState()PLearn::PLearner [virtual]
run()PLearn::Object [virtual]
sampleweightPLearn::NNet
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
setTrainingSet(VMat training_set, bool call_forget=true)PLearn::NNet [virtual]
setTrainStatsCollector(PP< VecStatsCollector > statscol)PLearn::PLearner [virtual]
setValidationSet(VMat validset)PLearn::PLearner [virtual]
stagePLearn::PLearner
store_bag_inputsPLearn::NNet [protected]
store_bag_sizePLearn::NNet [protected]
sub_test(VMat testset, PP< VecStatsCollector > test_stats, bool rtestoutputs, bool rtestcosts) const PLearn::PLearner [virtual]
targetPLearn::NNet
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_costfPLearn::NNet [mutable]
test_costsPLearn::NNet [protected]
test_minibatch_sizePLearn::PLearner
train()PLearn::NNet [virtual]
train_setPLearn::PLearner [protected]
train_statsPLearn::PLearner [protected]
training_costPLearn::NNet [protected]
transpose_first_hidden_layerPLearn::NNet
unref() const PLearn::PPointable [inline]
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]
v1PLearn::NNet
v2PLearn::NNet
validation_setPLearn::PLearner [protected]
verbosityPLearn::PLearner
w1PLearn::NNet
w2PLearn::NNet
wdirectPLearn::NNet
weight_decayPLearn::NNet
weightsize() const PLearn::PLearner [virtual]
weightsize_PLearn::PLearner [protected]
woutPLearn::NNet
wrecPLearn::NNet
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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