public class MultiLayerNetwork extends AbstractClassifier
| Modifier and Type | Class and Description |
|---|---|
static class |
MultiLayerNetwork.Aggregation |
static class |
MultiLayerNetwork.BiasType |
static class |
MultiLayerNetwork.Transfer |
Algorithm.EdgeDirectionmode, OUTPUTERRORALGORITHM, PREDICT, TRAINFactoryALGORITHMARRAY, COMPRESSED, DECOMPRESSED, DIFFERENCE, DIMENSION, HASH, IGNORENAN, INPUT, PREDICTED, RMSE, SOURCE, TARGET, WEIGHTDESCRIPTION| Constructor and Description |
|---|
MultiLayerNetwork(int... neuronCount) |
MultiLayerNetwork(MultiLayerNetwork.Aggregation aggregation,
int... neuronCount) |
MultiLayerNetwork(MultiLayerNetwork.Aggregation aggregation,
MultiLayerNetwork.BiasType bias,
int... neuronCount) |
MultiLayerNetwork(MultiLayerNetwork.Aggregation aggregation,
MultiLayerNetwork.Transfer transfer,
int... neuronCount) |
MultiLayerNetwork(MultiLayerNetwork.Aggregation aggregation,
MultiLayerNetwork.Transfer transfer,
MultiLayerNetwork.BiasType biasType,
int... neurons) |
MultiLayerNetwork(MultiLayerNetwork.Aggregation aggregationInput,
MultiLayerNetwork.Transfer transferInput,
MultiLayerNetwork.BiasType biasInput,
MultiLayerNetwork.Aggregation aggregationDefault,
MultiLayerNetwork.Transfer transferDefault,
MultiLayerNetwork.BiasType biasDefault,
MultiLayerNetwork.Aggregation aggregationOutput,
MultiLayerNetwork.Transfer transferOutput,
MultiLayerNetwork.BiasType biasOutput,
int... hiddenNeurons) |
| Modifier and Type | Method and Description |
|---|---|
void |
addDesiredOutputMatrix(Matrix m) |
void |
addInputMatrix(Matrix m) |
int |
determineOptimalTrainingDuration(ListDataSet dataSet,
int numberOfSteps) |
Classifier |
emptyCopy() |
NetworkLayer |
getInputLayer() |
Variable |
getInputVariable() |
double |
getLearningRate() |
List<NetworkLayer> |
getNetworkLayerList() |
Variable |
getOutputDeviationVariable() |
NetworkLayer |
getOutputLayer() |
Matrix |
getOutputMatrix() |
Variable |
getOutputVariable() |
Matrix |
predictOne(Matrix input) |
void |
reset() |
void |
setDesiredOutputVariable(Variable v) |
void |
setInputVariable(Variable v) |
void |
setLearningRate(double v) |
void |
setOutputDeviationVariable(Variable v) |
void |
setOutputVariable(Variable v) |
void |
setSampleWeight(double weight) |
void |
trainAll(ListDataSet dataSet) |
void |
trainOnce(ListDataSet dataSet) |
void |
trainOne(Matrix input,
Matrix sampleWeight,
Matrix desiredOutput) |
getClassCount, getFeatureCount, getInputLabel, getMode, getOutputErrorAlgorithm, getTargetLabel, getWeightLabel, isDiscrete, predictAll, predictOne, setInputLabel, setMode, setOutputErrorAlgorithm, setTargetLabel, setWeightLabel, trainOne, trainOneaddVariableKey, calculate, calculate, calculate, calculate, calculateObjects, calculateObjects, calculateObjects, clear, getAlgorithmMap, getDataSetMap, getDescription, getEdgeDirection, getEdgeLabel, getId, getInputKeys, getLabel, getLabelObject, getOutputKeys, getVariableKeys, getVariableMap, setAlgorithm, setDescription, setEdgeDirection, setEdgeLabel, setId, setLabel, setVariable, setVariables, toStringclone, fireValueChanged, getCoreObjectId, getGUIObject, showGUIequals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, waitgetClassCount, getFeatureCount, getInputLabel, getTargetLabel, isDiscrete, predictAll, predictOne, trainOne, trainOneclone, getCoreObjectIdfireValueChanged, getGUIObject, showGUIpublic MultiLayerNetwork(MultiLayerNetwork.Aggregation aggregationInput, MultiLayerNetwork.Transfer transferInput, MultiLayerNetwork.BiasType biasInput, MultiLayerNetwork.Aggregation aggregationDefault, MultiLayerNetwork.Transfer transferDefault, MultiLayerNetwork.BiasType biasDefault, MultiLayerNetwork.Aggregation aggregationOutput, MultiLayerNetwork.Transfer transferOutput, MultiLayerNetwork.BiasType biasOutput, int... hiddenNeurons)
public MultiLayerNetwork(int... neuronCount)
public MultiLayerNetwork(MultiLayerNetwork.Aggregation aggregation, MultiLayerNetwork.Transfer transfer, int... neuronCount)
public MultiLayerNetwork(MultiLayerNetwork.Aggregation aggregation, MultiLayerNetwork.BiasType bias, int... neuronCount)
public MultiLayerNetwork(MultiLayerNetwork.Aggregation aggregation, int... neuronCount)
public MultiLayerNetwork(MultiLayerNetwork.Aggregation aggregation, MultiLayerNetwork.Transfer transfer, MultiLayerNetwork.BiasType biasType, int... neurons)
public void setOutputVariable(Variable v)
public void setOutputDeviationVariable(Variable v)
public void setLearningRate(double v)
public double getLearningRate()
public void reset()
public NetworkLayer getOutputLayer()
public NetworkLayer getInputLayer()
public Variable getInputVariable()
public void setInputVariable(Variable v)
public void setDesiredOutputVariable(Variable v)
public void addInputMatrix(Matrix m)
public void setSampleWeight(double weight)
public void addDesiredOutputMatrix(Matrix m)
public Variable getOutputVariable()
public Variable getOutputDeviationVariable()
public List<NetworkLayer> getNetworkLayerList()
public Matrix getOutputMatrix()
public void trainOne(Matrix input, Matrix sampleWeight, Matrix desiredOutput)
trainOne in interface RegressortrainOne in class AbstractRegressorpublic int determineOptimalTrainingDuration(ListDataSet dataSet, int numberOfSteps) throws Exception
Exceptionpublic void trainAll(ListDataSet dataSet)
public void trainOnce(ListDataSet dataSet) throws Exception
Exceptionpublic Classifier emptyCopy()
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