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probabilistic changed

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Shin
2016-05-08 12:58:39 +02:00
parent 383bfa994b
commit e61a0888cf
1 changed files with 7 additions and 8 deletions
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15
include/NeuralNetwork/ConstructiveAlgorithms/CascadeCorrelation.h
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@@ -28,7 +28,7 @@ namespace NeuralNetwork {
_epoch = 0; _epoch = 0;
float error; float error;
if(_useProbabilisticOutputWeightSearch) { if(_maxRandomOutputWeights) {
error = trainOutputsRandom(0, network, patterns); error = trainOutputsRandom(0, network, patterns);
} else { } else {
error = trainOutputs(network, patterns); error = trainOutputs(network, patterns);
@@ -40,7 +40,7 @@ namespace NeuralNetwork {
addBestCandidate(network, candidate); addBestCandidate(network, candidate);
if(_useProbabilisticOutputWeightSearch) { if(_maxRandomOutputWeights) {
error = trainOutputsRandom(0, network, patterns); error = trainOutputsRandom(0, network, patterns);
} else { } else {
error = trainOutputs(network, patterns); error = trainOutputs(network, patterns);
@@ -75,12 +75,12 @@ namespace NeuralNetwork {
_activFunction = std::shared_ptr<ActivationFunction::ActivationFunction>(function.clone()); _activFunction = std::shared_ptr<ActivationFunction::ActivationFunction>(function.clone());
} }
void setProbabilisticOutputWeightSearch(bool status) { void setProbabilisticOutputWeightSearch(std::size_t number) {
_useProbabilisticOutputWeightSearch = status; _maxRandomOutputWeights = number;
} }
bool getProbabilisticOutputWeightSearch() const { std::size_t getProbabilisticOutputWeightSearch() const {
return _useProbabilisticOutputWeightSearch; return _maxRandomOutputWeights;
} }
std::size_t getEpochs() const { std::size_t getEpochs() const {
@@ -92,11 +92,10 @@ namespace NeuralNetwork {
float _minimalErrorStep = 0.00005; float _minimalErrorStep = 0.00005;
float _maxError; float _maxError;
float _weightRange; float _weightRange;
bool _useProbabilisticOutputWeightSearch = false;
std::size_t _epoch = 0; std::size_t _epoch = 0;
std::size_t _maxHiddenUnits = 20; std::size_t _maxHiddenUnits = 20;
std::size_t _maxRandomOutputWeights = 20; std::size_t _maxRandomOutputWeights = 0;
std::size_t _numberOfCandidates; std::size_t _numberOfCandidates;
std::size_t _maxOutpuLearningIterations = 1000; std::size_t _maxOutpuLearningIterations = 1000;
std::size_t _maxOutpuLearningIterationsWithoutChange = 5; std::size_t _maxOutpuLearningIterationsWithoutChange = 5;