// Number of features used for tweet prediction

int numberOfFeatures;

// Number of samples in training data

int numberOfSamples;

// A numberOfSamples X numberOfFeatures training data matrix that will be

// used to train TweetPredictor

double[][] X;

// Actual value of parameter for each sample of training data

double[] y;

double[] average;

double[] range;

public TrainingData(String filePath) throws IOException {

System.out.println("Starting Reading Data");

Scanner st = new Scanner(new BufferedReader(new FileReader(filePath)));

this.numberOfSamples = st.nextInt();

int originalFeatures = st.nextInt();

int extraFeatures = (originalFeatures*(originalFeatures - 1))/2;

this.numberOfFeatures = originalFeatures + extraFeatures;

X = new double[numberOfSamples][1 + numberOfFeatures];

y = new double[numberOfSamples];

average = new double[1 + numberOfFeatures];

range = new double[1 + numberOfFeatures];

for (int i = 0; i < numberOfSamples; i++) {

X[i][0] = 1;

double numberOfFollowers = st.nextDouble();

X[i][1] = numberOfFollowers;

int j = 2;

for (; j < 1 + numberOfFeatures - extraFeatures; j++) {

X[i][j] = st.nextDouble();

}

for (int k = 1; k <= originalFeatures; k++) {

for (int l = k+1; l <= originalFeatures; l++) {

X[i][j++] = X[i][k] * X[i][l];

}

}

y[i] = st.nextDouble();

}

System.out.println("Done Reading Data");

System.out.println("Starting Normalization");

normalizeFeatures();

System.out.println("Done Normalizing Data");

}

public void normalizeFeatures() throws IOException {

average[0] = 1;

range[0] = 1;

for (int j = 1; j <= numberOfFeatures; j++) {

double avg = 0;

double max = Integer.MIN_VALUE, min = Integer.MAX_VALUE;

for (int i = 0; i < numberOfSamples; i++) {

avg = avg + X[i][j] / numberOfSamples;

max = Math.max(X[i][j], max);

min = Math.min(X[i][j], min);

}

average[j] = avg;

range[j] = Math.max((max - min), 1);

for (int i = 0; i < numberOfSamples; i++) {

X[i][j] = (X[i][j] - average[j]) / range[j];

}

}

}

public void print() {

for (int i = 0; i < X.length; i++) {

for (int j = 0; j < X[0].length; j++) {

System.out.print(X[i][j] + " ");

}

System.out.println(y[i]);

System.out.println();

}

}