public class DSMGenerator extends LVQ1
alpha_0, ALPHA_DEFAULT_VALUE, chosenRandomIndex, IALPHA, randomIndexesinitial, initialset, iterations, numberOfPrototypesGeneratedalgorithmName, generatedDataSet, SEED, seedDefaultValueList, trainingDataSet| Constructor and Description |
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DSMGenerator(PrototypeSet tDataSet,
int nIter,
double percSize,
double alpha_0)
DSMGenerator constructor.
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DSMGenerator(PrototypeSet tDataSet,
int nIter,
int nProt,
double alpha_0)
DSMGenerator constructor.
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DSMGenerator(PrototypeSet tDataSet,
Parameters param)
DSMGenerator constructor.
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| Modifier and Type | Method and Description |
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protected void |
correct(Prototype i,
PrototypeSet tData)
Corrects the instance using a particular method
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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 wich contains the test data set.
3: Number of iterations.
4: Number of prototypes to be generated.
5: Alpha constant parameter.
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protected void |
penalize(Prototype m,
Prototype x)
Applies a DSMGenerator-reward to prototype m.
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protected void |
reward(Prototype m,
Prototype x)
Applies a DSMGenerator-reward to prototype m.
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extract, initDataSet, initDataSetRandomModereduceSetabsoluteAccuracy, 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, showResultsOfAccuracypublic DSMGenerator(PrototypeSet tDataSet, int nIter, int nProt, double alpha_0)
tDataSet - Training data set to be reduced.nIter - Number of iterations to be executed.nProt - Number of prototypes to be generated.alpha_0 - Alpha0 constant parameter of the algorithm.public DSMGenerator(PrototypeSet tDataSet, int nIter, double percSize, double alpha_0)
tDataSet - Training data set to be reduced.nIter - Number of iterations to be executed.percSize - Reduced size respect training set size.alpha_0 - Alpha0 constant parameter of the algorithm.public DSMGenerator(PrototypeSet tDataSet, Parameters param)
tDataSet - Training data set to be reduced.param - Parameters of the algorithm (number of iterations and prototypes, alpha0).protected void reward(Prototype m, Prototype x)
protected void penalize(Prototype m, Prototype x)
protected void correct(Prototype i, PrototypeSet tData)
public static void main(java.lang.String[] args)
args - Arguments of the main function.