, including all inherited members.
_classname_() | PLearn::IncrementalNNet | [static] |
_getOptionList_() | PLearn::IncrementalNNet | [static] |
_getRemoteMethodMap_() | PLearn::IncrementalNNet | [static] |
_isa_(const Object *o) | PLearn::IncrementalNNet | [static] |
_new_instance_for_typemap_() | PLearn::IncrementalNNet | [static] |
_static_initialize_() | PLearn::IncrementalNNet | [static] |
_static_initializer_ | PLearn::IncrementalNNet | [static] |
act | PLearn::IncrementalNNet | |
asString() const | PLearn::Object | [virtual] |
asStringRemoteTransmit() const | PLearn::Object | [virtual] |
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] |
batchComputeOutputAndConfidence(VMat inputs, real probability, VMat outputs_and_confidence) const | PLearn::PLearner | [virtual] |
boosting | PLearn::IncrementalNNet | |
build() | PLearn::IncrementalNNet | [virtual] |
build_() | PLearn::IncrementalNNet | [private] |
build_from_train_set() | PLearn::PLearner | [inline, protected, virtual] |
call(const string &methodname, int nargs, PStream &io) | PLearn::Object | [virtual] |
candidate_unit_bias | PLearn::IncrementalNNet | [protected] |
candidate_unit_internal_weight_gradients | PLearn::IncrementalNNet | [protected] |
candidate_unit_internal_weights | PLearn::IncrementalNNet | [protected] |
candidate_unit_output_weight_gradients | PLearn::IncrementalNNet | [protected] |
candidate_unit_output_weights | PLearn::IncrementalNNet | [protected] |
candidate_unit_weight_gradients | PLearn::IncrementalNNet | [protected] |
candidate_unit_weights | PLearn::IncrementalNNet | [protected] |
changeOption(const string &optionname, const string &value) | PLearn::Object | |
changeOptions(const map< string, string > &name_value) | PLearn::Object | [virtual] |
classname() const | PLearn::IncrementalNNet | [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::IncrementalNNet | [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::IncrementalNNet | [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] |
connection_gradient_threshold | PLearn::IncrementalNNet | |
connection_removing_threshold | PLearn::IncrementalNNet | |
cost_type | PLearn::IncrementalNNet | |
current_average_cost | PLearn::IncrementalNNet | [protected] |
current_example | PLearn::IncrementalNNet | [protected] |
decay_factor | PLearn::IncrementalNNet | |
declareMethods(RemoteMethodMap &rmm) | PLearn::PLearner | [protected, static] |
declareOptions(OptionList &ol) | PLearn::IncrementalNNet | [protected, static] |
declaringFile() | PLearn::IncrementalNNet | [inline, static] |
deepCopy(CopiesMap &copies) const | PLearn::IncrementalNNet | [virtual] |
deepCopyNoMap() | PLearn::Object | |
direct_weight_gradients | PLearn::IncrementalNNet | [protected] |
direct_weights | PLearn::IncrementalNNet | [protected] |
enable_internal_weights | PLearn::IncrementalNNet | |
expdir | PLearn::PLearner | |
finalize() | PLearn::PLearner | [virtual] |
finalized | PLearn::PLearner | |
forget() | PLearn::IncrementalNNet | [virtual] |
forget_when_training_set_changes | PLearn::PLearner | [protected] |
getExperimentDirectory() const | PLearn::PLearner | [inline] |
getOption(const string &optionname) const | PLearn::Object | |
getOptionList() const | PLearn::IncrementalNNet | [virtual] |
getOptionMap() const | PLearn::IncrementalNNet | [virtual] |
getOptionsToRemoteTransmit() const | PLearn::Object | [virtual] |
getOptionsToSave() const | PLearn::Object | [virtual] |
getOutputNames() const | PLearn::PLearner | [virtual] |
getRemoteMethodMap() const | PLearn::IncrementalNNet | [virtual] |
getTestCostIndex(const string &costname) const | PLearn::PLearner | |
getTestCostNames() const | PLearn::IncrementalNNet | [virtual] |
getTrainCostIndex(const string &costname) const | PLearn::PLearner | |
getTrainCostNames() const | PLearn::IncrementalNNet | [virtual] |
getTrainingSet() const | PLearn::PLearner | [inline] |
getTrainStatsCollector() | PLearn::PLearner | [inline] |
getValidationSet() const | PLearn::PLearner | [inline] |
h | PLearn::IncrementalNNet | |
hard_activation_function | PLearn::IncrementalNNet | |
hasOption(const string &optionname) const | PLearn::Object | |
hidden_layer_biases | PLearn::IncrementalNNet | [protected] |
hidden_layer_weight_gradients | PLearn::IncrementalNNet | [protected] |
hidden_layer_weights | PLearn::IncrementalNNet | [protected] |
incremental_connections | PLearn::IncrementalNNet | |
IncrementalNNet() | PLearn::IncrementalNNet | |
info() const | PLearn::Object | [virtual] |
inherited typedef | PLearn::IncrementalNNet | [private] |
initial_learning_rate | PLearn::IncrementalNNet | |
initTrain() | PLearn::PLearner | [protected] |
inputsize() const | PLearn::PLearner | [virtual] |
inputsize_ | PLearn::PLearner | [protected] |
internal_weight_gradients | PLearn::IncrementalNNet | [protected] |
internal_weights | PLearn::IncrementalNNet | [protected] |
isStatefulLearner() const | PLearn::PLearner | [virtual] |
learning_rate | PLearn::IncrementalNNet | [protected] |
linear_output | PLearn::IncrementalNNet | |
load(const PPath &filename) | PLearn::Object | [virtual] |
makeDeepCopyFromShallowCopy(CopiesMap &copies) | PLearn::IncrementalNNet | [virtual] |
master_sends_testset_rows | PLearn::PLearner | |
max_n_epochs_to_fail | PLearn::IncrementalNNet | |
minibatch_size | PLearn::IncrementalNNet | |
minimize_local_cost | PLearn::IncrementalNNet | |
moving_average_coefficient | PLearn::IncrementalNNet | [protected] |
n_examples | PLearn::PLearner | [protected] |
n_examples_seen | PLearn::IncrementalNNet | [protected] |
n_examples_training_candidate | PLearn::IncrementalNNet | [protected] |
n_outputs | PLearn::IncrementalNNet | |
newread(PStream &in, unsigned int id=UINT_MAX) | PLearn::Object | |
newwrite(PStream &out) const | PLearn::Object | [virtual] |
next_average_cost | PLearn::IncrementalNNet | [protected] |
nservers | PLearn::PLearner | |
nstages | PLearn::PLearner | |
nTestCosts() const | PLearn::PLearner | [virtual] |
nTrainCosts() const | PLearn::PLearner | [virtual] |
Object(bool call_build_=false) | PLearn::Object | |
oldread(istream &in) | PLearn::Object | [virtual] |
online | PLearn::IncrementalNNet | |
output_biases | PLearn::IncrementalNNet | [protected] |
output_cost_type | PLearn::IncrementalNNet | |
output_loss(const Vec &output, const Vec &target) const | PLearn::IncrementalNNet | [virtual] |
output_loss_gradient(const Vec &output, const Vec &target, Vec output_gradient, real sampleweight) const | PLearn::IncrementalNNet | [virtual] |
output_weight_decay | PLearn::IncrementalNNet | |
output_weight_gradients | PLearn::IncrementalNNet | [protected] |
output_weights | PLearn::IncrementalNNet | [protected] |
outputsize() const | PLearn::IncrementalNNet | [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 | |
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] |
rand_range | PLearn::IncrementalNNet | |
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] |
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] |
residual_correlation_gradient | PLearn::IncrementalNNet | |
residual_correlation_output_gradient(Vec MAgradients, const Vec &weights, const Vec &output_gradient, real activation, real &hidden_gradient) const | PLearn::IncrementalNNet | |
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 | |
sub_test(VMat testset, PP< VecStatsCollector > test_stats, bool rtestoutputs, bool rtestcosts) const | PLearn::PLearner | [virtual] |
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_size | PLearn::PLearner | |
train() | PLearn::IncrementalNNet | [virtual] |
train_set | PLearn::PLearner | [protected] |
train_stats | PLearn::PLearner | [protected] |
unref() const | PLearn::PPointable | [inline] |
update_incremental_connections(Vec weights, Vec MAgradients, const Vec &input, real gradient) const | PLearn::IncrementalNNet | |
usage() const | PLearn::PPointable | [inline] |
use(VMat testset, VMat outputs) const | PLearn::PLearner | [virtual] |
use_a_separate_random_generator_for_testing | PLearn::PLearner | |
use_hinge_loss_for_hard_activation | PLearn::IncrementalNNet | |
useOnTrain(Mat &outputs) const | PLearn::PLearner | [virtual] |
validation_set | PLearn::PLearner | [protected] |
verbosity | PLearn::PLearner | |
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] |