/** Classifies the test set */
public void classifyTest() {
// Start of training time
Timer.resetTime();
classifyTestSet();
// End of test time
Timer.setTestTime();
// Showing results
System.out.println(name + " " + relation + " Test " + Timer.getTestTime() + "s");
} // end-method
/** Generates the model of the algorithm */
public void generateModel() {
double newEpsilon;
// Start of model time
Timer.resetTime();
double term = 0.7 / (double) (nClasses - 1);
// Initialization of the membership matrix
// 0.7 is assigned to the labeled instance in the training
// set. 0.3 is split between the rest of classes
for (int i = 0; i < trainData.length; i++) {
Arrays.fill(membership[i], term);
membership[i][trainOutput[i]] = 0.3;
}
epsilon = Double.MAX_VALUE;
newEpsilon = Double.MAX_VALUE;
int iterations = 0;
do {
epsilon = newEpsilon;
computeCentroids();
newEpsilon = computeMembership();
System.out.println("Iteration " + iterations + " Error: " + newEpsilon);
iterations++;
} while ((Math.abs(epsilon - newEpsilon) > delta) && (iterations < maxIterations));
// End of model time
Timer.setModelTime();
// Showing results
System.out.println(name + " " + relation + " Model " + Timer.getModelTime() + "s");
} // end-method
