public static void printNeighbors(ArrayList neighbors) {
int i = 0;
for(Neighbor neighbor : neighbors) {
Instance instance = neighbor.getInstance();
System.out.println("\nNeighbor " + (i + 1) + ", distance: " + neighbor.getDistance());
i++;
for(Feature f : instance.getAttributes()) {
System.out.print(f.getName() + ": ");
if(f instanceof Category) {
System.out.println(((Category)f).getCategory().toString());
}
else if(f instanceof Distance) {
System.out.println(((Distance)f).getDistance().toString());
}
else if (f instanceof Expiration) {
System.out.println(((Expiration)f).getExpiry().toString());
}
else if (f instanceof Handset) {
System.out.print(((Handset)f).getOs().toString() + ", ");
System.out.println(((Handset)f).getDevice().toString());
}
else if (f instanceof Offer) {
System.out.println(((Offer)f).getOfferType().toString());
}
else if (f instanceof WSAction) {
System.out.println(((WSAction)f).getAction().toString());
}
}
}
}
public static void main(String[] args) {
ArrayList instances = null;
ArrayList distances = null;
ArrayList neighbors = null;
WSAction.Action classification = null;
Instance classificationInstance = null;
FileReader reader = null;
int numRuns = 0, truePositives = 0, falsePositives = 0, falseNegatives = 0, trueNegatives = 0;
double precision = 0, recall = 0, fMeasure = 0;
falsePositives = 1;
reader = new FileReader(PATH_TO_DATA_FILE);
instances = reader.buildInstances();
do {
classificationInstance = extractIndividualInstance(instances);
distances = calculateDistances(instances, classificationInstance);
neighbors = getNearestNeighbors(distances);
classification = determineMajority(neighbors);
System.out.println("Gathering " + K + " nearest neighbors to:");
printClassificationInstance(classificationInstance);
printNeighbors(neighbors);
System.out.println("\nExpected situation result for instance: " + classification.toString());
if(classification.toString().equals(((WSAction)classificationInstance.getAttributes().get(WSACTION_INDEX)).getAction().toString())) {
truePositives++;
}
else {
falseNegatives++;
}
numRuns++;
instances.add(classificationInstance);
} while(numRuns < NUM_RUNS);
precision = ((double)(truePositives / (double)(truePositives + falsePositives)));
recall = ((double)(truePositives / (double)(truePositives + falseNegatives)));
fMeasure = ((double)(precision * recall) / (double)(precision + recall));
System.out.println("Precision: " + precision);
System.out.println("Recall: " + recall);
System.out.println("F-Measure: " + fMeasure);
System.out.println("Average distance: " + (double)(averageDistance / (double)(NUM_RUNS * K)));
}
public static void printClassificationInstance(Instance classificationInstance) {
for(Feature f : classificationInstance.getAttributes()) {
System.out.print(f.getName() + ": ");
if(f instanceof Category) {
System.out.println(((Category)f).getCategory().toString());
}
else if(f instanceof Distance) {
System.out.println(((Distance)f).getDistance().toString());
}
else if (f instanceof Expiration) {
System.out.println(((Expiration)f).getExpiry().toString());
}
else if (f instanceof Handset) {
System.out.print(((Handset)f).getOs().toString() + ", ");
System.out.println(((Handset)f).getDevice().toString());
}
else if (f instanceof Offer) {
System.out.println(((Offer)f).getOfferType().toString());
}
else if (f instanceof WSAction) {
System.out.println(((WSAction)f).getAction().toString());
}
}
}