public class CNN extends PrototypeGenerator
| Modifier and Type | Field and Description |
|---|---|
protected int |
k
Neighborhood size in KNN
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algorithmName, generatedDataSet, SEED, seedDefaultValueList, trainingDataSet| Constructor and Description |
|---|
CNN(PrototypeSet _trainingDataSet)
Creates a CNN algorithm.
|
CNN(PrototypeSet _trainingDataSet,
int k)
Creates a CNN algorithm.
|
| Modifier and Type | Method and Description |
|---|---|
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 will contain the test data set
3: k Number of neighbors used in the KNN function
|
static PrototypeSet |
makeReductionOf(PrototypeSet original)
Make a selection by the CNN method.
|
static PrototypeSet |
makeReductionOf(PrototypeSet original,
int k)
Make a selection by the CNN method.
|
PrototypeSet |
reduceSet()
Makes the trivial reduction.
|
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, showResultsOfAccuracypublic CNN(PrototypeSet _trainingDataSet)
_trainingDataSet - original training data.public CNN(PrototypeSet _trainingDataSet, int k)
_trainingDataSet - original training data.k - Neighborhood size in KNNpublic static PrototypeSet makeReductionOf(PrototypeSet original)
original - Original data set.public static PrototypeSet makeReductionOf(PrototypeSet original, int k)
original - Original data set.k - K used in KNN-rule.public PrototypeSet reduceSet()
PrototypeGeneratorreduceSet in class PrototypeGeneratorpublic static void main(java.lang.String[] args)
args - Arguments of the main function.