JavaML
Interface IDataset

All Superinterfaces:
IOnlineDataset
All Known Implementing Classes:
DatasetDouble

public interface IDataset
extends IOnlineDataset

An interface for representing a Dataset It extends IOnlineDataset as it imposes several properties, such as the whole dataset being accesible at once.


Nested Class Summary
 
Nested classes/interfaces inherited from interface JavaML.IOnlineDataset
IOnlineDataset.DataType, IOnlineDataset.FeatureType
 
Method Summary
 IDataset getDataFeatureSubset(int[] featuresRequired)
           
 double[][] getDataMatrixDouble()
           
 IDataset getDataSampleSubset(int[] samplesRequired)
           
 double[] getDataWeights()
           
 IDataset getSampledDataset(double[] distributionOverFeatures, int sampleSize)
           
 double[] getSampleDouble(int sampleNumber, boolean hasTarget)
           
 int[] getTargetVector()
           
 int getTotalWeight()
           
 IDataset returnSampledTestingSet(int foldNumber, int sampleSize)
           
 IDataset returnSampledTrainingSet(int foldNumber, int sampleSize)
           
 IDataset returnWeightedTestingSet(int foldNumber)
           
 IDataset returnWeightedTrainingSet(int foldNumber)
           
 void setDataWeights(double[] newWeights)
           
 void splitIntoFolds(int numberOfFolds)
           
 
Methods inherited from interface JavaML.IOnlineDataset
getDataType, getNextDataPoint, getNextTarget, getNumberOfFeatures, getNumberOfSamples, hasData, resetDataset, returnCurrentDataSampleNumber, returnCurrentTargetSampleNumber, setRandomSeed
 

Method Detail

getDataMatrixDouble

double[][] getDataMatrixDouble()

getTargetVector

int[] getTargetVector()

getSampleDouble

double[] getSampleDouble(int sampleNumber,
                         boolean hasTarget)

getDataWeights

double[] getDataWeights()

setDataWeights

void setDataWeights(double[] newWeights)

getTotalWeight

int getTotalWeight()

getDataFeatureSubset

IDataset getDataFeatureSubset(int[] featuresRequired)

getDataSampleSubset

IDataset getDataSampleSubset(int[] samplesRequired)

getSampledDataset

IDataset getSampledDataset(double[] distributionOverFeatures,
                           int sampleSize)

splitIntoFolds

void splitIntoFolds(int numberOfFolds)

returnWeightedTrainingSet

IDataset returnWeightedTrainingSet(int foldNumber)

returnWeightedTestingSet

IDataset returnWeightedTestingSet(int foldNumber)

returnSampledTrainingSet

IDataset returnSampledTrainingSet(int foldNumber,
                                  int sampleSize)

returnSampledTestingSet

IDataset returnSampledTestingSet(int foldNumber,
                                 int sampleSize)