experimentshell.knn.java Source code

Introduction

Here is the source code for experimentshell.knn.java

Source

package experimentshell;

import weka.classifiers.Classifier;
import weka.core.Instance;
import weka.core.Instances;
import static java.lang.Math.abs;
import static java.lang.Math.pow;
import java.util.Map;
import java.util.TreeMap;

/*
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/**
 *
 * @author mormon
 */
public class knn extends Classifier {

    Integer k = 8;
    Instances data;

    @Override
    public void buildClassifier(Instances i) throws Exception {
        data = i;
    }

    @Override
    public double classifyInstance(Instance instance) throws Exception {
        // sorting happens automatically with a TreeMap
        Map<Integer, Double> distances = new TreeMap<>();
        int distance = 0;

        // iterate through the data and determine the distance
        for (int i = 0; i < data.numInstances(); i++) {
            for (int j = 0; j < data.numAttributes(); j++) {
                // this is the Manhattan distance
                distance += abs((int) (data.instance(i).value(j) - instance.value(j)));
                // the Euclidean distance
                // distance += pow((int)(data.instance(i).value(j) - instance.value(j)), 2);
            }
            distances.put(distance, data.instance(i).classValue());
            distance = 0;
        }

        // find the majority class of the nearest neighbor
        int count = 0;
        double tempClass;
        int tally[] = new int[data.numClasses()];
        // use k instances to find the majority class and assign that instance
        for (Map.Entry<Integer, Double> entry : distances.entrySet()) {
            if (count >= k)
                break;
            tempClass = entry.getValue();
            tally[(int) tempClass]++;
            count++;
        }

        int maxIndex = 0;
        int majority;
        for (int i = 0; i < data.numClasses(); i++) {
            majority = tally[i];
            if (majority > tally[maxIndex]) {
                maxIndex = i;
            }
        }

        return maxIndex;
    }
}