public class MixtGaussGenerator extends PrototypeGenerator
Modifier and Type | Field and Description |
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protected int |
numberOfClass |
protected int |
numberOfPrototypes |
algorithmName, generatedDataSet, SEED, seedDefaultValueList, trainingDataSet
Constructor and Description |
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MixtGaussGenerator(PrototypeSet _trainingDataSet,
int blocks,
java.lang.String choice)
Build a new PSOGenerator Algorithm
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MixtGaussGenerator(PrototypeSet t,
Parameters parameters)
Build a new MixtGaussGenerator Algorithm
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Modifier and Type | Method and Description |
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double[] |
CalculateAccuracy(PrototypeSet actual)
Accuracy per class.
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Pair<PrototypeSet,PrototypeSet> |
EMstep(PrototypeSet actual,
PrototypeSet SD)
Expectation-Maximisation Algorithm
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double |
f_x(double x,
double mu,
double sigma)
F(x) = N(x^t_k)
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static void |
main(java.lang.String[] args)
General main for all the prototoype generators
Arguments:
0: Filename with the training data set to be condensed.
1: Filename which contains the test data set.
3: Seed of the random number generator.
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double |
pdfNormal(double x)
Return the value of PDF normal.
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PrototypeSet |
reduceSet()
Generate a reduced prototype set by the MixtGaussGenerator method.
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absoluteAccuracy, absoluteAccuracyAndError, absoluteAccuracyKNN, accuracy, accuracy2, desordenar_vector_sin, desordenar_vector, execute, generateReducedDataSet, getResultingAccuracy, getResultingAccuracy, getResults, getResultsOfAccuracy, getResultsOfAccuracy, getSeed, getSetSizeFromPercentage, getSetSizeFromPercentage, getTime, inic_vector_sin, inic_vector, saveResultsOfAccuracyIn, saveResultsOfAccuracyIn, selecRandomSet, setSeed, showResultsOfAccuracy, showResultsOfAccuracy
protected int numberOfPrototypes
protected int numberOfClass
public MixtGaussGenerator(PrototypeSet _trainingDataSet, int blocks, java.lang.String choice)
public MixtGaussGenerator(PrototypeSet t, Parameters parameters)
t
- Original prototype set to be reduced.parameters
- Parameters of the algorithm (only % of reduced set).public double pdfNormal(double x)
x
- public double f_x(double x, double mu, double sigma)
x
- public double[] CalculateAccuracy(PrototypeSet actual)
public Pair<PrototypeSet,PrototypeSet> EMstep(PrototypeSet actual, PrototypeSet SD)
public PrototypeSet reduceSet()
reduceSet
in class PrototypeGenerator
public static void main(java.lang.String[] args)
args
- Arguments of the main function.