PLearn 0.1
PLearn::NatGradNNet Member List
This is the complete list of members for PLearn::NatGradNNet, including all inherited members.
_classname_()PLearn::NatGradNNet [static]
_getOptionList_()PLearn::NatGradNNet [static]
_getRemoteMethodMap_()PLearn::NatGradNNet [static]
_isa_(const Object *o)PLearn::NatGradNNet [static]
_new_instance_for_typemap_()PLearn::NatGradNNet [static]
_static_initialize_()PLearn::NatGradNNet [static]
_static_initializer_PLearn::NatGradNNet [static]
activation_statistics_moving_average_coefficientPLearn::NatGradNNet
activations_scalingPLearn::NatGradNNet [protected]
all_mparamsPLearn::NatGradNNet [private]
all_paramsPLearn::NatGradNNet [private]
all_params_deltaPLearn::NatGradNNet [private]
all_params_gradientPLearn::NatGradNNet [private]
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]
biasesPLearn::NatGradNNet [protected]
build()PLearn::NatGradNNet [virtual]
build_()PLearn::NatGradNNet [private]
build_from_train_set()PLearn::PLearner [inline, protected, virtual]
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]
classname() const PLearn::NatGradNNet [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::NatGradNNet [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::NatGradNNet [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::NatGradNNet [virtual]
computeOutputsAndCosts(const Mat &input, const Mat &target, Mat &output, Mat &costs) const PLearn::NatGradNNet [virtual]
cumulative_training_timePLearn::NatGradNNet [protected]
declareMethods(RemoteMethodMap &rmm)PLearn::PLearner [protected, static]
declareOptions(OptionList &ol)PLearn::NatGradNNet [protected, static]
declaringFile()PLearn::NatGradNNet [inline, static]
deepCopy(CopiesMap &copies) const PLearn::NatGradNNet [virtual]
deepCopyNoMap()PLearn::Object
example_weightsPLearn::NatGradNNet [private]
expdirPLearn::PLearner
fbpropLoss(const Mat &output, const Mat &target, const Vec &example_weights, Mat &train_costs) const PLearn::NatGradNNet [protected]
finalize()PLearn::PLearner [virtual]
finalizedPLearn::PLearner
forget()PLearn::NatGradNNet [virtual]
forget_when_training_set_changesPLearn::PLearner [protected]
fpropNet(int n_examples, bool during_training) const PLearn::NatGradNNet [protected]
full_natgradPLearn::NatGradNNet
getExperimentDirectory() const PLearn::PLearner [inline]
getOption(const string &optionname) const PLearn::Object
getOptionList() const PLearn::NatGradNNet [virtual]
getOptionMap() const PLearn::NatGradNNet [virtual]
getOptionsToRemoteTransmit() const PLearn::Object [virtual]
getOptionsToSave() const PLearn::Object [virtual]
getOutputNames() const PLearn::PLearner [virtual]
getRemoteMethodMap() const PLearn::NatGradNNet [virtual]
getTestCostIndex(const string &costname) const PLearn::PLearner
getTestCostNames() const PLearn::NatGradNNet [virtual]
getTrainCostIndex(const string &costname) const PLearn::PLearner
getTrainCostNames() const PLearn::NatGradNNet [virtual]
getTrainingSet() const PLearn::PLearner [inline]
getTrainStatsCollector()PLearn::PLearner [inline]
getValidationSet() const PLearn::PLearner [inline]
group_paramsPLearn::NatGradNNet [private]
group_params_deltaPLearn::NatGradNNet [private]
group_params_gradientPLearn::NatGradNNet [private]
hasOption(const string &optionname) const PLearn::Object
hidden_layer_sizesPLearn::NatGradNNet
info() const PLearn::Object [virtual]
inherited typedefPLearn::NatGradNNet [private]
init_lratePLearn::NatGradNNet
initTrain()PLearn::PLearner [protected]
input_size_lrate_normalization_powerPLearn::NatGradNNet
inputsize() const PLearn::PLearner [virtual]
inputsize_PLearn::PLearner [protected]
isStatefulLearner() const PLearn::PLearner [virtual]
layer_mparamsPLearn::NatGradNNet
layer_paramsPLearn::NatGradNNet
layer_params_deltaPLearn::NatGradNNet [private]
layer_params_gradientPLearn::NatGradNNet [private]
layer_sizesPLearn::NatGradNNet [protected]
load(const PPath &filename)PLearn::Object [virtual]
lrate_decayPLearn::NatGradNNet
lrate_scale_factorPLearn::NatGradNNet
lrate_scale_factor_max_powerPLearn::NatGradNNet
lrate_scale_factor_min_powerPLearn::NatGradNNet
makeDeepCopyFromShallowCopy(CopiesMap &copies)PLearn::NatGradNNet [virtual]
master_sends_testset_rowsPLearn::PLearner
mean_activationsPLearn::NatGradNNet [protected]
minibatch_sizePLearn::NatGradNNet
mweightsPLearn::NatGradNNet [protected]
n_examplesPLearn::PLearner [protected]
n_layersPLearn::NatGradNNet [protected]
NatGradNNet()PLearn::NatGradNNet
neuron_extended_outputs_per_layerPLearn::NatGradNNet [mutable, private]
neuron_gradientsPLearn::NatGradNNet [private]
neuron_gradients_per_layerPLearn::NatGradNNet [private]
neuron_outputs_per_layerPLearn::NatGradNNet [mutable, private]
neurons_natgrad_per_layerPLearn::NatGradNNet
neurons_natgrad_templatePLearn::NatGradNNet
newread(PStream &in, unsigned int id=UINT_MAX)PLearn::Object
newwrite(PStream &out) const PLearn::Object [virtual]
noutputsPLearn::NatGradNNet
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]
onlineStep(int t, const Mat &targets, Mat &train_costs, Vec example_weights)PLearn::NatGradNNet [protected]
output_layer_L1_penalty_factorPLearn::NatGradNNet
output_layer_lrate_scalePLearn::NatGradNNet
output_typePLearn::NatGradNNet
outputsize() const PLearn::NatGradNNet [virtual]
parallelize_herePLearn::PLearner
params_averaging_coeffPLearn::NatGradNNet
params_averaging_freqPLearn::NatGradNNet
params_natgrad_per_groupPLearn::NatGradNNet
params_natgrad_per_input_templatePLearn::NatGradNNet
params_natgrad_templatePLearn::NatGradNNet
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
PLearner()PLearn::PLearner
PPointable()PLearn::PPointable [inline]
PPointable(const PPointable &other)PLearn::PPointable [inline]
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_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]
save(const PPath &filename) const PLearn::Object [virtual]
save_trainingset_prefixPLearn::PLearner
seed_PLearn::PLearner
self_adjusted_scaling_and_biasPLearn::NatGradNNet
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::PLearner [virtual]
setTrainStatsCollector(PP< VecStatsCollector > statscol)PLearn::PLearner [virtual]
setValidationSet(VMat validset)PLearn::PLearner [virtual]
stagePLearn::PLearner
sub_test(VMat testset, PP< VecStatsCollector > test_stats, bool rtestoutputs, bool rtestcosts) const PLearn::PLearner [virtual]
target_mean_activationPLearn::NatGradNNet
target_stdev_activationPLearn::NatGradNNet
targetsPLearn::NatGradNNet [private]
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::NatGradNNet [virtual]
train_costsPLearn::NatGradNNet [private]
train_setPLearn::PLearner [protected]
train_statsPLearn::PLearner [protected]
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]
validation_setPLearn::PLearner [protected]
var_activationsPLearn::NatGradNNet [protected]
verbosityPLearn::PLearner
weightsPLearn::NatGradNNet [protected]
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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