PLearn::NeuralNet Member List

This is the complete list of members for PLearn::NeuralNet, including all inherited members.

_classname_()	PLearn::Object	[static]
_getOptionList_()	PLearn::Object	[static]
_isa_(Object *o)	PLearn::Object	[static]
_new_instance_for_typemap_()	PLearn::Object	[static]
_static_initialize_()	PLearn::Object	[static]
_static_initializer_	PLearn::Object	[static]
appendMeasurer(Measurer &measurer)	PLearn::Learner	[inline]
apply(const VMat &data, VMat outputs)	PLearn::Learner	[virtual]
applyAndComputeCosts(const VMat &data, VMat outputs, VMat costs)	PLearn::Learner	[virtual]
applyAndComputeCostsOnTestMat(const VMat &test_set, int i, const Mat &output_block, const Mat &cost_block)	PLearn::Learner	[virtual]
avg_objective	PLearn::Learner
avgsq_objective	PLearn::Learner
basename() const	PLearn::Learner
batch_size	PLearn::NeuralNet
best_step	PLearn::Learner
bias_decay	PLearn::NeuralNet
build()	PLearn::NeuralNet	[virtual]
build_()	PLearn::NeuralNet	[private]
call(const string &methodname, int nargs, PStream &in_parameters, PStream &out_results)	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::Object	[virtual]
computeCost(const Vec &inputvec, const Vec &targetvec, const Vec &outputvec, const Vec &costvec)	PLearn::NeuralNet	[virtual]
computeCosts(const VVec &input, VVec &target, VVec &weight, Vec &costs)	PLearn::Learner	[virtual]
computeCosts(const VMat &data, VMat costs)	PLearn::Learner	[virtual]
computeCostsFromOutputs(const VVec &input, const Vec &output, const VVec &target, const VVec &weight, Vec &costs)	PLearn::Learner	[virtual]
computeLeaveOneOutCosts(const VMat &data, VMat costs)	PLearn::Learner	[virtual]
computeLeaveOneOutCosts(const VMat &data, VMat costsmat, CostFunc costf)	PLearn::Learner	[virtual]
computeOutput(const VVec &input, Vec &output)	PLearn::Learner	[virtual]
computeOutputAndCosts(const VVec &input, VVec &target, const VVec &weight, Vec &output, Vec &costs)	PLearn::Learner	[virtual]
computeTestStatistics(const VMat &costs)	PLearn::Learner
cost	PLearn::NeuralNet	[protected]
cost_funcs	PLearn::NeuralNet
costf	PLearn::NeuralNet
costNames() const	PLearn::NeuralNet	[virtual]
costs	PLearn::NeuralNet	[protected]
costsize() const	PLearn::NeuralNet	[virtual]
costweights	PLearn::NeuralNet	[protected]
declareOptions(OptionList &ol)	PLearn::NeuralNet	[protected, static]
deepCopy(CopiesMap &copies) const	PLearn::Object	[virtual]
default_vlog()	PLearn::Learner	[static]
direct_in_to_out	PLearn::NeuralNet
direct_in_to_out_weight_decay	PLearn::NeuralNet
distributed_	PLearn::Learner	[protected]
dont_parallelize	PLearn::Learner
each_cpu_saves_its_errors	PLearn::Learner	[protected]
earlystop_max_degradation	PLearn::Learner
earlystop_max_degraded_steps	PLearn::Learner
earlystop_min_improvement	PLearn::Learner
earlystop_min_value	PLearn::Learner
earlystop_minval	PLearn::Learner
earlystop_previousval	PLearn::Learner	[protected]
earlystop_relative_changes	PLearn::Learner
earlystop_save_best	PLearn::Learner
earlystop_testresultindex	PLearn::Learner
earlystop_testsetnum	PLearn::Learner
epoch() const	PLearn::Learner	[inline]
epoch_	PLearn::Learner	[protected]
expdir	PLearn::Learner	[protected]
experiment_name	PLearn::Learner
f	PLearn::NeuralNet
force_saving_on_all_processes	PLearn::Learner	[static]
forget()	PLearn::NeuralNet	[virtual]
freeTestResultsStreams()	PLearn::Learner	[protected]
getExperimentDirectory() const	PLearn::Learner	[inline]
getOption(const string &optionname) const	PLearn::Object
getOptionList() const	PLearn::Object	[virtual]
getOptionsToSave() const	PLearn::Object	[virtual]
getTestDuringTrain() const	PLearn::Learner	[inline]
getTestResultsStream(int k)	PLearn::Learner	[protected]
getTrainCost()	PLearn::Learner	[inline]
getTrainingSet()	PLearn::Learner	[inline]
getTrainObjectiveStream()	PLearn::Learner	[protected]
global_weight_decay	PLearn::NeuralNet
info() const	PLearn::Object	[virtual]
inherited typedef	PLearn::NeuralNet
initial_paramsvalues	PLearn::NeuralNet	[protected]
initializeParams()	PLearn::NeuralNet
input	PLearn::NeuralNet	[protected]
inputsize() const	PLearn::Learner	[inline]
inputsize_	PLearn::Learner
iseed	PLearn::NeuralNet
layer1_bias_decay	PLearn::NeuralNet
layer1_weight_decay	PLearn::NeuralNet
layer2_bias_decay	PLearn::NeuralNet
layer2_weight_decay	PLearn::NeuralNet
Learner(int the_inputsize=0, int the_targetsize=0, int the_outputsize=0)	PLearn::Learner
load(const string &filename="")	PLearn::Learner	[virtual]
makeDeepCopyFromShallowCopy(CopiesMap &copies)	PLearn::NeuralNet	[virtual]
measure(int step, const Vec &costs)	PLearn::Learner	[virtual]
PLearn::Measurer::measure(int t)	PLearn::Measurer	[inline, virtual]
measure_cpu_time_first	PLearn::Learner	[protected]
measurers	PLearn::Learner	[protected]
minibatch_size	PLearn::Learner
nepochs	PLearn::NeuralNet
NeuralNet()	PLearn::NeuralNet
newread(PStream &in)	PLearn::Object
newtest(VMat testset, VecStatsCollector &test_stats, VMat testoutputs=0, VMat testcosts=0)	PLearn::Learner	[virtual]
newtrain(VecStatsCollector &train_stats)	PLearn::Learner	[virtual]
newwrite(PStream &out) const	PLearn::Object
nhidden	PLearn::NeuralNet
nhidden2	PLearn::NeuralNet
normalization	PLearn::NeuralNet
Object()	PLearn::Object
objectiveout	PLearn::Learner
oldread(istream &in)	PLearn::Learner	[virtual]
oldwrite(ostream &out) const	PLearn::Learner	[virtual]
openTestResultsStreams()	PLearn::Learner	[protected]
openTrainObjectiveStream()	PLearn::Learner	[protected]
optimizer	PLearn::NeuralNet
options	PLearn::Learner
output	PLearn::NeuralNet	[protected]
output_and_target_to_cost	PLearn::NeuralNet
output_layer_bias_decay	PLearn::NeuralNet
output_layer_weight_decay	PLearn::NeuralNet
output_transfer_func	PLearn::NeuralNet
outputResultLineToFile(const string &filename, const Vec &results, bool append, const string &names)	PLearn::Learner	[protected]
outputsize() const	PLearn::Learner	[inline]
outputsize_	PLearn::Learner
params	PLearn::NeuralNet	[protected]
paramsvalues	PLearn::NeuralNet	[protected]
PLEARN_DECLARE_ABSTRACT_OBJECT(Learner)	PLearn::Learner
PLEARN_DECLARE_OBJECT(NeuralNet)	PLearn::NeuralNet
PPointable()	PLearn::PPointable	[inline]
PPointable(const PPointable &other)	PLearn::PPointable	[inline]
prepareToSendResults(PStream &out, int nres)	PLearn::Object	[inline, protected]
print(ostream &out) const	PLearn::Object	[virtual]
read(istream &in)	PLearn::Object	[virtual]
readOptionVal(PStream &in, const string &optionname)	PLearn::Object
ref() const	PLearn::PPointable	[inline]
report_test_progress_every	PLearn::Learner
run()	PLearn::Object	[virtual]
save(const string &filename="") const	PLearn::Learner	[virtual]
save_at_every_epoch	PLearn::Learner
save_objective	PLearn::Learner
saveparams	PLearn::NeuralNet
semisupervised_flatten_factor	PLearn::NeuralNet
semisupervised_prior	PLearn::NeuralNet
setEarlyStopping(int which_testset, int which_testresult, real max_degradation, real min_value=-FLT_MAX, real min_improvement=0, bool relative_changes=true, bool save_best=true, int max_degraded_steps=-1)	PLearn::Learner
setExperimentDirectory(const string &the_expdir)	PLearn::Learner	[virtual]
setModel(const Vec &new_options)	PLearn::Learner	[virtual]
setOption(const string &optionname, const string &value)	PLearn::Object
setTestCostFunctions(Array< CostFunc > costfunctions)	PLearn::Learner	[inline]
setTestDuringTrain(ostream &testout, int every, Array< VMat > testsets)	PLearn::Learner	[virtual]
setTestDuringTrain(Array< VMat > testsets)	PLearn::Learner	[virtual]
setTestStatistics(StatsItArray statistics)	PLearn::Learner	[inline]
setTrainCost(Vec &cost)	PLearn::Learner	[inline, protected]
setTrainingSet(VMat training_set)	PLearn::Learner	[inline, virtual]
stop_if_wanted()	PLearn::Learner	[virtual]
target	PLearn::NeuralNet	[protected]
target_and_weights	PLearn::NeuralNet	[protected]
targetsize() const	PLearn::Learner	[inline]
targetsize_	PLearn::Learner
test(VMat test_set, const string &save_test_outputs="", const string &save_test_costs="")	PLearn::Learner	[virtual]
test_costfuncs	PLearn::Learner
test_every	PLearn::Learner
test_results_streams	PLearn::Learner	[protected]
test_sets	PLearn::Learner
test_statistics	PLearn::Learner
testout	PLearn::Learner
testResultsNames()	PLearn::NeuralNet	[inline, virtual]
PLearn::Learner::testResultsNames() const	PLearn::Learner	[virtual]
tmpvec	PLearn::Learner	[protected]
train(VMat training_set)	PLearn::NeuralNet	[virtual]
PLearn::Learner::train(VMat training_set, VMat accept_prob, real max_accept_prob=1.0, VMat weights=VMat())	PLearn::Learner	[inline, virtual]
train_cost	PLearn::Learner	[protected]
train_objective_stream	PLearn::Learner	[protected]
train_set	PLearn::Learner
trainObjectiveNames() const	PLearn::Learner	[virtual]
unref() const	PLearn::PPointable	[inline]
usage() const	PLearn::PPointable	[inline]
use(const Vec &inputvec, Vec &prediction)	PLearn::NeuralNet	[virtual]
PLearn::Learner::use(const Mat &inputs, Mat outputs)	PLearn::Learner	[inline, virtual]
use_file_if_bigger	PLearn::Learner	[static]
useAndCost(const Vec &inputvec, const Vec &targetvec, Vec outputvec, Vec costvec)	PLearn::NeuralNet	[virtual]
useAndCostOnTestVec(const VMat &test_set, int i, const Vec &output, const Vec &cost)	PLearn::Learner	[virtual]
vec_input	PLearn::Learner
vlog	PLearn::Learner
w1	PLearn::NeuralNet	[protected]
w2	PLearn::NeuralNet	[protected]
wdirect	PLearn::NeuralNet	[protected]
weight_decay	PLearn::NeuralNet
weightsize() const	PLearn::Learner	[inline]
weightsize_	PLearn::Learner
wout	PLearn::NeuralNet	[protected]
write(ostream &out) const	PLearn::Object	[virtual]
writeOptionVal(PStream &out, const string &optionname) const	PLearn::Object
~Learner()	PLearn::Learner	[virtual]
~Measurer()	PLearn::Measurer	[virtual]
~NeuralNet()	PLearn::NeuralNet	[virtual]
~Object()	PLearn::Object	[virtual]
~PPointable()	PLearn::PPointable	[inline, virtual]

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