, including all inherited members.
_classname_() | PLearn::FeatureSetNNet | [static] |
_getOptionList_() | PLearn::FeatureSetNNet | [static] |
_getRemoteMethodMap_() | PLearn::FeatureSetNNet | [static] |
_isa_(const Object *o) | PLearn::FeatureSetNNet | [static] |
_new_instance_for_typemap_() | PLearn::FeatureSetNNet | [static] |
_static_initialize_() | PLearn::FeatureSetNNet | [static] |
_static_initializer_ | PLearn::FeatureSetNNet | [static] |
add_affine_transform(Vec input, Mat weights, Vec bias, Vec output, bool input_is_sparse, bool output_is_sparse, Vec output_indices=Vec(0)) const | PLearn::FeatureSetNNet | [protected] |
add_transfer_func(const Vec &input, string transfer_func="default") const | PLearn::FeatureSetNNet | [protected] |
asString() const | PLearn::Object | [virtual] |
asStringRemoteTransmit() const | PLearn::Object | [virtual] |
b1 | PLearn::FeatureSetNNet | |
b2 | PLearn::FeatureSetNNet | |
b_costs | PLearn::PLearner | [mutable, protected] |
b_inputs | PLearn::PLearner | [mutable, protected] |
b_outputs | PLearn::PLearner | [mutable, protected] |
b_targets | PLearn::PLearner | [mutable, protected] |
b_weights | PLearn::PLearner | [mutable, protected] |
batch_size | PLearn::FeatureSetNNet | |
batchComputeOutputAndConfidence(VMat inputs, real probability, VMat outputs_and_confidence) const | PLearn::FeatureSetNNet | [protected, virtual] |
bias_decay | PLearn::FeatureSetNNet | |
bout | PLearn::FeatureSetNNet | |
bout_dist_rep | PLearn::FeatureSetNNet | |
bprop(Vec &inputv, Vec &outputv, Vec &targetv, Vec &costsv, real learning_rate, real sampleweight=1) | PLearn::FeatureSetNNet | [protected] |
build() | PLearn::FeatureSetNNet | [virtual] |
build_() | PLearn::FeatureSetNNet | [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] |
classification_loss(const Vec &outputv, int target) const | PLearn::FeatureSetNNet | [private] |
classname() const | PLearn::FeatureSetNNet | [virtual] |
clearProppathGradient() | PLearn::FeatureSetNNet | [protected] |
compute_softmax(const Vec &x, const Vec &y) const | PLearn::FeatureSetNNet | [private] |
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::FeatureSetNNet | [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::FeatureSetNNet | [virtual] |
computeOutputAndCosts(const Vec &input, const Vec &target, Vec &output, Vec &costs) const | PLearn::FeatureSetNNet | [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_funcs | PLearn::FeatureSetNNet | |
declareMethods(RemoteMethodMap &rmm) | PLearn::PLearner | [protected, static] |
declareOptions(OptionList &ol) | PLearn::FeatureSetNNet | [protected, static] |
declaringFile() | PLearn::FeatureSetNNet | [inline, static] |
decrease_constant | PLearn::FeatureSetNNet | |
deepCopy(CopiesMap &copies) const | PLearn::FeatureSetNNet | [virtual] |
deepCopyNoMap() | PLearn::Object | |
direct_bout | PLearn::FeatureSetNNet | |
direct_in_to_out | PLearn::FeatureSetNNet | |
direct_in_to_out_weight_decay | PLearn::FeatureSetNNet | |
direct_wout | PLearn::FeatureSetNNet | |
dist_rep_dim | PLearn::FeatureSetNNet | |
expdir | PLearn::PLearner | |
f | PLearn::FeatureSetNNet | [mutable, private] |
feat_input | PLearn::FeatureSetNNet | [mutable, protected] |
feat_sets | PLearn::FeatureSetNNet | |
feats | PLearn::FeatureSetNNet | [mutable, private] |
feats_since_last_update | PLearn::FeatureSetNNet | [protected] |
FeatureSetNNet() | PLearn::FeatureSetNNet | |
fillWeights(const Mat &weights) | PLearn::FeatureSetNNet | [protected] |
finalize() | PLearn::PLearner | [virtual] |
finalized | PLearn::PLearner | |
fixed_output_weights | PLearn::FeatureSetNNet | |
forget() | PLearn::FeatureSetNNet | [virtual] |
forget_when_training_set_changes | PLearn::PLearner | [protected] |
fprop(const Vec &inputv, Vec &outputv, const Vec &targetv, Vec &costsv, real sampleweight=1) const | PLearn::FeatureSetNNet | [protected] |
fpropCostsFromOutput(const Vec &inputv, const Vec &outputv, const Vec &targetv, Vec &costsv, real sampleweight=1) const | PLearn::FeatureSetNNet | [protected] |
fpropOutput(const Vec &inputv, Vec &outputv) const | PLearn::FeatureSetNNet | [protected] |
getExperimentDirectory() const | PLearn::PLearner | [inline] |
getOption(const string &optionname) const | PLearn::Object | |
getOptionList() const | PLearn::FeatureSetNNet | [virtual] |
getOptionMap() const | PLearn::FeatureSetNNet | [virtual] |
getOptionsToRemoteTransmit() const | PLearn::Object | [virtual] |
getOptionsToSave() const | PLearn::Object | [virtual] |
getOutputNames() const | PLearn::PLearner | [virtual] |
getRemoteMethodMap() const | PLearn::FeatureSetNNet | [virtual] |
getTestCostIndex(const string &costname) const | PLearn::PLearner | |
getTestCostNames() const | PLearn::FeatureSetNNet | [virtual] |
getTrainCostIndex(const string &costname) const | PLearn::PLearner | |
getTrainCostNames() const | PLearn::FeatureSetNNet | [virtual] |
getTrainingSet() const | PLearn::PLearner | [inline] |
getTrainStatsCollector() | PLearn::PLearner | [inline] |
getValidationSet() const | PLearn::PLearner | [inline] |
grad | PLearn::FeatureSetNNet | [mutable, private] |
gradient | PLearn::FeatureSetNNet | [mutable, private] |
gradient_act_hidden2v | PLearn::FeatureSetNNet | [protected] |
gradient_act_hiddenv | PLearn::FeatureSetNNet | [protected] |
gradient_act_outputv | PLearn::FeatureSetNNet | [protected] |
gradient_affine_transform(Vec input, Mat weights, Vec bias, Vec ginput, Mat gweights, Vec gbias, Vec goutput, bool input_is_sparse, bool output_is_sparse, real learning_rate, real weight_decay, real bias_decay, Vec output_indices=Vec(0)) | PLearn::FeatureSetNNet | [protected] |
gradient_b1 | PLearn::FeatureSetNNet | |
gradient_b2 | PLearn::FeatureSetNNet | |
gradient_bout | PLearn::FeatureSetNNet | |
gradient_bout_dist_rep | PLearn::FeatureSetNNet | |
gradient_direct_bout | PLearn::FeatureSetNNet | |
gradient_direct_wout | PLearn::FeatureSetNNet | |
gradient_feat_input | PLearn::FeatureSetNNet | [protected] |
gradient_hidden2v | PLearn::FeatureSetNNet | [protected] |
gradient_hiddenv | PLearn::FeatureSetNNet | [protected] |
gradient_last_layer | PLearn::FeatureSetNNet | [mutable, private] |
gradient_nnet_input | PLearn::FeatureSetNNet | [protected] |
gradient_outputv | PLearn::FeatureSetNNet | [protected] |
gradient_penalty(Vec input, Mat weights, Vec bias, Mat gweights, Vec gbias, bool input_is_sparse, bool output_is_sparse, real learning_rate, real weight_decay, real bias_decay, Vec output_indices=Vec(0)) | PLearn::FeatureSetNNet | [protected] |
gradient_transfer_func(Vec &output, Vec &gradient_input, Vec &gradient_output, string transfer_func="default", int nll_softmax_speed_up_target=-1) | PLearn::FeatureSetNNet | [protected] |
gradient_w1 | PLearn::FeatureSetNNet | |
gradient_w2 | PLearn::FeatureSetNNet | |
gradient_wout | PLearn::FeatureSetNNet | |
gradient_wout_dist_rep | PLearn::FeatureSetNNet | |
hasOption(const string &optionname) const | PLearn::Object | |
hidden2v | PLearn::FeatureSetNNet | [protected] |
hidden_transfer_func | PLearn::FeatureSetNNet | |
hiddenv | PLearn::FeatureSetNNet | [protected] |
id | PLearn::FeatureSetNNet | [mutable, private] |
ifeats | PLearn::FeatureSetNNet | [mutable, private] |
info() const | PLearn::Object | [virtual] |
inherited typedef | PLearn::FeatureSetNNet | [private] |
initialization_method | PLearn::FeatureSetNNet | |
initializeParams(bool set_seed=true) | PLearn::FeatureSetNNet | [protected, virtual] |
initTrain() | PLearn::PLearner | [protected] |
inputsize() const | PLearn::PLearner | [virtual] |
inputsize_ | PLearn::PLearner | [protected] |
isStatefulLearner() const | PLearn::PLearner | [virtual] |
last_layer | PLearn::FeatureSetNNet | [mutable, private] |
layer1_bias_decay | PLearn::FeatureSetNNet | |
layer1_weight_decay | PLearn::FeatureSetNNet | |
layer2_bias_decay | PLearn::FeatureSetNNet | |
layer2_weight_decay | PLearn::FeatureSetNNet | |
load(const PPath &filename) | PLearn::Object | [virtual] |
makeDeepCopyFromShallowCopy(CopiesMap &copies) | PLearn::FeatureSetNNet | [virtual] |
margin | PLearn::FeatureSetNNet | |
master_sends_testset_rows | PLearn::PLearner | |
my_argmax(const Vec &vec, int default_compare=0) const | PLearn::FeatureSetNNet | [private] |
n_examples | PLearn::PLearner | [protected] |
n_feat_sets | PLearn::FeatureSetNNet | [protected] |
newread(PStream &in, unsigned int id=UINT_MAX) | PLearn::Object | |
newwrite(PStream &out) const | PLearn::Object | [virtual] |
nfeats | PLearn::FeatureSetNNet | [mutable, private] |
nhidden | PLearn::FeatureSetNNet | |
nhidden2 | PLearn::FeatureSetNNet | |
ni | PLearn::FeatureSetNNet | [mutable, private] |
nj | PLearn::FeatureSetNNet | [mutable, private] |
nk | PLearn::FeatureSetNNet | [mutable, private] |
nll(const Vec &outputv, int target) const | PLearn::FeatureSetNNet | [private] |
nnet_input | PLearn::FeatureSetNNet | [mutable, protected] |
nservers | PLearn::PLearner | |
nstages | PLearn::PLearner | |
nTestCosts() const | PLearn::PLearner | [virtual] |
nTrainCosts() const | PLearn::PLearner | [virtual] |
Object(bool call_build_=false) | PLearn::Object | |
offset | PLearn::FeatureSetNNet | [mutable, private] |
oldread(istream &in) | PLearn::Object | [virtual] |
output_comp | PLearn::FeatureSetNNet | [mutable, private] |
output_empirical_distribution | PLearn::FeatureSetNNet | |
output_gradient_verification(Vec grad, Vec est_grad) | PLearn::FeatureSetNNet | [protected] |
output_layer_bias_decay | PLearn::FeatureSetNNet | |
output_layer_dist_rep_bias_decay | PLearn::FeatureSetNNet | |
output_layer_dist_rep_weight_decay | PLearn::FeatureSetNNet | |
output_layer_weight_decay | PLearn::FeatureSetNNet | |
output_transfer_func | PLearn::FeatureSetNNet | |
outputsize() const | PLearn::FeatureSetNNet | [virtual] |
parallelize_here | PLearn::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 | |
penalty_type | PLearn::FeatureSetNNet | |
PLearner() | PLearn::PLearner | |
possible_targets_vary | PLearn::FeatureSetNNet | |
PPointable() | PLearn::PPointable | [inline] |
PPointable(const PPointable &other) | PLearn::PPointable | [inline] |
prepareToSendResults(PStream &out, int nres) | PLearn::Object | [static] |
processDataSet(VMat dataset) const | PLearn::FeatureSetNNet | [protected, virtual] |
pval1 | PLearn::FeatureSetNNet | [mutable, private] |
pval2 | PLearn::FeatureSetNNet | [mutable, private] |
pval3 | PLearn::FeatureSetNNet | [mutable, private] |
pval4 | PLearn::FeatureSetNNet | [mutable, private] |
pval5 | PLearn::FeatureSetNNet | [mutable, private] |
random_gen | PLearn::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] |
reind_target | PLearn::FeatureSetNNet | [mutable, protected] |
remote_test(VMat testset, PP< VecStatsCollector > test_stats, bool rtestoutputs, bool rtestcosts) const | PLearn::PLearner | [virtual] |
remote_useOnTrain() const | PLearn::PLearner | [virtual] |
report_progress | PLearn::PLearner | |
resetInternalState() | PLearn::PLearner | [virtual] |
rgen | PLearn::FeatureSetNNet | [protected] |
row | PLearn::FeatureSetNNet | [mutable, private] |
run() | PLearn::Object | [virtual] |
save(const PPath &filename) const | PLearn::Object | [virtual] |
save_trainingset_prefix | PLearn::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::PLearner | [virtual] |
setTrainStatsCollector(PP< VecStatsCollector > statscol) | PLearn::PLearner | [virtual] |
setValidationSet(VMat validset) | PLearn::PLearner | [virtual] |
stage | PLearn::PLearner | |
start_learning_rate | PLearn::FeatureSetNNet | |
stochastic_gradient_descent_speedup | PLearn::FeatureSetNNet | |
str | PLearn::FeatureSetNNet | [mutable, private] |
sub_test(VMat testset, PP< VecStatsCollector > test_stats, bool rtestoutputs, bool rtestcosts) const | PLearn::PLearner | [virtual] |
target_values | PLearn::FeatureSetNNet | [mutable, private] |
target_values_reference_set | PLearn::FeatureSetNNet | [mutable, protected] |
target_values_since_last_update | PLearn::FeatureSetNNet | [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::FeatureSetNNet | [protected, virtual] |
test_minibatch_size | PLearn::PLearner | |
total_feats_per_token | PLearn::FeatureSetNNet | [protected] |
total_output_size | PLearn::FeatureSetNNet | [protected] |
total_updates | PLearn::FeatureSetNNet | [protected] |
train() | PLearn::FeatureSetNNet | [virtual] |
train_set | PLearn::PLearner | [protected] |
train_stats | PLearn::PLearner | [protected] |
unref() const | PLearn::PPointable | [inline] |
update() | PLearn::FeatureSetNNet | [protected] |
update_affine_transform(Vec input, Mat weights, Vec bias, Mat gweights, Vec gbias, bool input_is_sparse, bool output_is_sparse, Vec output_indices) | PLearn::FeatureSetNNet | [protected] |
usage() const | PLearn::PPointable | [inline] |
use(VMat testset, VMat outputs) const | PLearn::FeatureSetNNet | [protected, virtual] |
use_a_separate_random_generator_for_testing | PLearn::PLearner | |
useOnTrain(Mat &outputs) const | PLearn::PLearner | [virtual] |
val | PLearn::FeatureSetNNet | [mutable, private] |
val2 | PLearn::FeatureSetNNet | [mutable, private] |
val_string_reference_set | PLearn::FeatureSetNNet | [mutable, protected] |
validation_set | PLearn::PLearner | [protected] |
verbosity | PLearn::PLearner | |
verify_gradient(Vec &input, Vec target, real step) | PLearn::FeatureSetNNet | [protected] |
verify_gradient_affine_transform(Vec global_input, Vec &global_output, Vec &global_targetv, Vec &global_costs, real sampleweight, Vec input, Mat weights, Vec bias, Mat est_gweights, Vec est_gbias, bool input_is_sparse, bool output_is_sparse, real step, Vec output_indices=Vec(0)) const | PLearn::FeatureSetNNet | [protected] |
w1 | PLearn::FeatureSetNNet | |
w2 | PLearn::FeatureSetNNet | |
weight_decay | PLearn::FeatureSetNNet | |
weightsize() const | PLearn::PLearner | [virtual] |
weightsize_ | PLearn::PLearner | [protected] |
wout | PLearn::FeatureSetNNet | |
wout_dist_rep | PLearn::FeatureSetNNet | |
write(ostream &out) const | PLearn::Object | [virtual] |
writeOptionVal(PStream &out, const string &optionname) const | PLearn::Object | |
~FeatureSetNNet() | PLearn::FeatureSetNNet | [virtual] |
~Object() | PLearn::Object | [virtual] |
~PPointable() | PLearn::PPointable | [inline, virtual] |