|
||||||||||
PREV NEXT | FRAMES NO FRAMES |
Packages that use DataSet | |
---|---|
org.neuroph.core | Provides base classes and basic building components for neural networks. |
org.neuroph.core.learning | Provides base classes for neural network learning algorithms. |
org.neuroph.nnet.learning | Provides implementations of specific neural network learning algorithms. |
org.neuroph.util | Provides various utility classes for creating neural networks, type codes, parsing vectors, etc. |
org.neuroph.util.norm | Provides data normalization techniques |
Uses of DataSet in org.neuroph.core |
---|
Methods in org.neuroph.core with parameters of type DataSet | |
---|---|
void |
NeuralNetwork.learn(DataSet trainingSet)
Learn the specified training set |
void |
NeuralNetwork.learn(DataSet trainingSet,
LearningRule learningRule)
Learn the specified training set, using specified learning rule |
void |
NeuralNetwork.learnInNewThread(DataSet trainingSet)
Starts learning in a new thread to learn the specified training set, and immediately returns from method to the current thread execution |
void |
NeuralNetwork.learnInNewThread(DataSet trainingSet,
LearningRule learningRule)
Starts learning with specified learning rule in new thread to learn the specified training set, and immediately returns from method to the current thread execution |
Uses of DataSet in org.neuroph.core.learning |
---|
Methods in org.neuroph.core.learning that return DataSet | |
---|---|
static DataSet |
DataSet.createFromFile(String filePath,
int inputsCount,
int outputsCount,
String delimiter)
|
DataSet[] |
DataSet.createTrainingAndTestSubsets(int trainSetPercent,
int testSetPercent)
Returns output vector size of training elements in this training set This method is implementation of EngineIndexableSet interface, and it is added to provide compatibility with Encog data sets and FlatNetwork |
DataSet |
LearningRule.getTrainingSet()
Gets training set |
static DataSet |
DataSet.load(String filePath)
Loads training set from the specified file |
Methods in org.neuroph.core.learning with parameters of type DataSet | |
---|---|
void |
UnsupervisedLearning.doLearningEpoch(DataSet trainingSet)
This method does one learning epoch for the unsupervised learning rules. |
void |
SupervisedLearning.doLearningEpoch(DataSet trainingSet)
This method implements basic logic for one learning epoch for the supervised learning algorithms. |
abstract void |
IterativeLearning.doLearningEpoch(DataSet trainingSet)
Override this method to implement specific learning epoch - one learning iteration, one pass through whole training set |
void |
IterativeLearning.doOneLearningIteration(DataSet trainingSet)
Runs one learning iteration for the specified training set and notfies observers. |
abstract void |
LearningRule.learn(DataSet trainingSet)
Override this method to implement specific learning procedures |
void |
IterativeLearning.learn(DataSet trainingSet)
|
void |
SupervisedLearning.learn(DataSet trainingSet,
double maxError)
Trains network for the specified training set and number of iterations |
void |
SupervisedLearning.learn(DataSet trainingSet,
double maxError,
int maxIterations)
Trains network for the specified training set and number of iterations |
void |
IterativeLearning.learn(DataSet trainingSet,
int maxIterations)
Trains network for the specified training set and number of iterations |
void |
LearningRule.setTrainingSet(DataSet trainingSet)
Sets training set for this learning rule |
Uses of DataSet in org.neuroph.nnet.learning |
---|
Methods in org.neuroph.nnet.learning with parameters of type DataSet | |
---|---|
void |
UnsupervisedHebbianLearning.doLearningEpoch(DataSet trainingSet)
This method does one learning epoch for the unsupervised learning rules. |
void |
SimulatedAnnealingLearning.doLearningEpoch(DataSet trainingSet)
Perform one simulated annealing epoch. |
void |
DynamicBackPropagation.doLearningEpoch(DataSet trainingSet)
|
void |
CompetitiveLearning.doLearningEpoch(DataSet trainingSet)
This method does one learning epoch for the unsupervised learning rules. |
void |
KohonenLearning.learn(DataSet trainingSet)
|
void |
HopfieldLearning.learn(DataSet trainingSet)
Calculates weights for the hopfield net to learn the specified training set |
Uses of DataSet in org.neuroph.util |
---|
Methods in org.neuroph.util that return DataSet | |
---|---|
static DataSet |
TrainingSetImport.importFromFile(String filePath,
int inputsCount,
int outputsCount,
String separator)
|
Uses of DataSet in org.neuroph.util.norm |
---|
Methods in org.neuroph.util.norm with parameters of type DataSet | |
---|---|
void |
Normalizer.normalize(DataSet dataSet)
Normalize specified training set |
void |
MaxNormalizer.normalize(DataSet dataSet)
|
void |
MaxMinNormalizer.normalize(DataSet dataSet)
|
void |
DecimalScaleNormalizer.normalize(DataSet dataSet)
|
|
||||||||||
PREV NEXT | FRAMES NO FRAMES |