/**
* Computes the mean rating that a user has given to movies.
*
* @param ratings Map of ratings for a particular user.
* @return Returns a double indicating the average rating.
*/
public static double calculateMean(Map<Integer, Rating> ratings) {
double sum = 0;
for (Rating r : ratings.values()) {
sum += r.getRating();
}
return sum / ratings.size();
}
public static void main(String[] args) {
// Maps that maps a user id to a subset of ratings given by that user.
Map<Integer, User> trainRatings = new HashMap<Integer, User>();
Map<Integer, User> testRatings = new HashMap<Integer, User>();
// Parse training and test data into maps.
System.out.println("1. Parsing DataSets");
parseRatings(trainRatings, "./DataSet/TrainingRatings.txt");
parseRatings(testRatings, "./DataSet/TestingRatings.txt");
// Fill Map of means.
System.out.println("2. Calculating Mean Values");
for (Integer uid : trainRatings.keySet()) {
trainRatings.get(uid).setMean(calculateMean(trainRatings.get(uid).getRatings()));
}
// Predict ratings for users.
System.out.println("3. Predicting Ratings");
int total = 0;
double errorAbsSum = 0;
double errorRootSum = 0;
for (Integer uid : testRatings.keySet()) {
// Predict movie ratings and determine error summation
for (Integer mid : testRatings.get(uid).getRatings().keySet()) {
Rating r = testRatings.get(uid).getRatings().get(mid);
double error =
r.getRating() - calculateWeightedSum(trainRatings, trainRatings.get(uid), mid);
errorAbsSum += Math.abs(error);
errorRootSum += Math.pow(error, 2);
total++;
}
}
// Compute accuracy of algorithm.
System.out.printf("Mean Absolute Error: %.2f\n", (errorAbsSum / total));
System.out.printf("Root Mean Squared Error: %.2f\n", (Math.sqrt(errorRootSum / total)));
}
/**
* Calculates the weight for two users over all items they share recorded ratings for.
*
* @param train User object for particular user in training data.
* @param test User object for active user.
* @return Returns a Double representing the computed weight.
*/
public static double calculateWeight(User train, User test) {
double numSum = 0;
double denTestSum = 0;
double denTrainSum = 0;
Map<Integer, Rating> ratings = train.getRatings();
for (Rating r : test.getRatings().values()) {
if (ratings.containsKey(r.getMovieId())) {
numSum +=
(r.getRating() - test.getMean())
* (ratings.get(r.getMovieId()).getRating() - train.getMean());
denTestSum += Math.pow(r.getRating() - test.getMean(), 2);
denTrainSum += Math.pow(ratings.get(r.getMovieId()).getRating() - train.getMean(), 2);
}
}
return (denTestSum == 0 || denTrainSum == 0) ? 0 : numSum / Math.sqrt(denTestSum * denTrainSum);
}