public class LVQTC extends LVQ1
alpha_0, ALPHA_DEFAULT_VALUE, chosenRandomIndex, IALPHA, randomIndexes
initial, initialset, iterations, numberOfPrototypesGenerated
algorithmName, generatedDataSet, SEED, seedDefaultValueList, trainingDataSet
Constructor and Description |
---|
LVQTC(PrototypeSet traDataSet,
int it,
double percProts,
double alpha_r,
double alpha_w,
int T,
int epoches)
Constructor based on the training dataset and the parameters
|
LVQTC(PrototypeSet traDataSet,
Parameters parameters)
Constructor based on the training dataset and the parameters
|
Modifier and Type | Method and Description |
---|---|
protected void |
correct(Prototype i,
PrototypeSet tData)
Corrects the instance using a particular method
|
protected PrototypeSet |
doEpoche(PrototypeSet outputDataSet) |
protected void |
initCounterOf(Prototype i) |
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
|
protected PrototypeSet |
neuronCreation(PrototypeSet data)
Creates new neurons.
|
protected PrototypeSet |
neuronPruning(PrototypeSet data)
Prunes the neurons which have their counting variables lesser
than the retention threshold.
|
protected void |
penalize(Prototype m,
Prototype x)
Applies LVQTC penalization to prototype m
|
PrototypeSet |
reduceSet()
Execute the method and returns the output instance set
|
protected void |
reward(Prototype m,
Prototype x)
Applies the LVQTC reward to prototype m
|
extract, initDataSet, initDataSetRandomMode
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
public LVQTC(PrototypeSet traDataSet, Parameters parameters)
public LVQTC(PrototypeSet traDataSet, int it, double percProts, double alpha_r, double alpha_w, int T, int epoches)
traDataSet
- Training data prototypesit
- Number of iterations that will execute the algorithm.percProts
- New size of the set (% of training data set).alpha_r
- Alpha algorithm parameter.alpha_w
- Alpha algorithm parameter.T
- Retention threshold of the algorithm.protected void initCounterOf(Prototype i)
protected void penalize(Prototype m, Prototype x)
protected void correct(Prototype i, PrototypeSet tData)
protected PrototypeSet neuronPruning(PrototypeSet data)
data
- prototype set.protected PrototypeSet neuronCreation(PrototypeSet data)
data
- prototype set.protected PrototypeSet doEpoche(PrototypeSet outputDataSet)
public PrototypeSet reduceSet()
reduceSet
in class LVQGenerator
public static void main(java.lang.String[] args)
args
- Arguments of the main function.