Answer to Question #233011 in Java | JSP | JSF for Zia

Question

You will be tasked to write this program in either C++ or Java, whichever you feel more comfortable with.

The goal is for the program to be able to guess the user's political party before they reach the end of the survey. This will require your program to gather a substantial amount of data before it can make accurate guesses. In particular:

2. The last question should ask which political party they affiliate with. This way you will be able to gather and store data corresponding to the results you acquire. Create at least 4 political party storage.

Answer 1

import java.io.*;
import weka.*;
 
public class Prediction {
	public static BufferedReader readDataFile(String file) {
		BufferedReader inp = null;
 
		try {
			inp = new BufferedReader(new FileReader(file));
		} catch (FileNotFoundException e) {
			System.err.println(e);
		}
 
		return inp;
	}
 
	public static Evaluation classify(Classifier model,
			Instances trainingSet, Instances testingSet) throws Exception {
		Evaluation eval = new Evaluation(trainingSet);
 
		model.buildClassifier(trainingSet);
		eval.evaluateModel(model, testingSet);
 
		return eval;
	}
 
	public static double calculateAccuracy(FastVector preds) {
		double ct = 0;
 
		for (int i = 0; i < preds.size(); i++) {
			NominalPrediction np = (NominalPrediction) preds.elementAt(i);
			if (np.predicted() == np.actual()) {
				ct++;
			}
		}
 
		return 100 * ct / preds.size();
	}
 
	public static Instances[][] crossValidationSplit(Instances data, int numberOfFolds) {
		Instances[][] split = new Instances[2][numberOfFolds];
 
		for (int i = 0; i < numberOfFolds; i++) {
			split[0][i] = data.trainCV(numberOfFolds, i);
			split[1][i] = data.testCV(numberOfFolds, i);
		}
 
		return split;
	}
 
	public static void main(String[] args) throws Exception {
		BufferedReader datafile = readDataFile("elections.txt");
 
		Instances data = new Instances(datafile);
		data.setClassIndex(data.numAttributes() - 1);
		Instances[][] split = crossValidationSplit(data, 10);
		Instances[] trainingSplits = split[0];
		Instances[] testingSplits = split[1];
 
		Classifier[] models = { 
				new J48(), 
				new PART(), 
				new DecisionTable(),
				new DecisionStump() 
		};
 
		for (int j = 0; j < models.length; j++) {
 
			FastVector preds = new FastVector();
 
			for (int i = 0; i < trainingSplits.length; i++) {
				Evaluation validation = classify(models[j], trainingSplits[i], testingSplits[i]);
 
				preds.appendElements(validation.preds());
			}
 
			double accuracy = calculateAccuracy(preds);
 
			System.out.println("Accuracy of " + models[j].getClass().getSimpleName() + ": "
					+ String.format("%.2f%%", accuracy)
					+ "\n---------------------------------");
		}
 
	}
}