Example #1
0
  @Override
  protected void buildModel() throws Exception {

    for (int iter = 1; iter <= numIters; iter++) {

      loss = 0;
      errs = 0;
      for (int s = 0, smax = numUsers * 100; s < smax; s++) {

        // randomly draw (u, i, j)
        int u = 0, i = 0, j = 0;

        while (true) {
          u = Randoms.uniform(numUsers);
          SparseVector pu = userCache.get(u);

          if (pu.getCount() == 0) continue;

          int[] is = pu.getIndex();
          i = is[Randoms.uniform(is.length)];

          do {
            j = Randoms.uniform(numItems);
          } while (pu.contains(j));

          break;
        }

        // update parameters
        double xui = predict(u, i);
        double xuj = predict(u, j);
        double xuij = xui - xuj;

        double vals = -Math.log(g(xuij));
        loss += vals;
        errs += vals;

        double cmg = g(-xuij);

        for (int f = 0; f < numFactors; f++) {
          double puf = P.get(u, f);
          double qif = Q.get(i, f);
          double qjf = Q.get(j, f);

          P.add(u, f, lRate * (cmg * (qif - qjf) - regU * puf));
          Q.add(i, f, lRate * (cmg * puf - regI * qif));
          Q.add(j, f, lRate * (cmg * (-puf) - regI * qjf));

          loss += regU * puf * puf + regI * qif * qif + regI * qjf * qjf;
        }
      }

      if (isConverged(iter)) break;
    }
  }
Example #2
0
  /**
   * Split ratings into k-fold.
   *
   * @param kfold number of folds
   */
  private void splitFolds(int kfold) {
    assert kfold > 0;

    assignMatrix = new SparseMatrix(rateMatrix);

    int numRates = rateMatrix.getData().length;
    numFold = kfold > numRates ? numRates : kfold;

    // divide rating data into kfold sample of equal size
    double[] rdm = new double[numRates];
    int[] fold = new int[numRates];
    double indvCount = (numRates + 0.0) / numFold;

    for (int i = 0; i < numRates; i++) {
      rdm[i] = Randoms.uniform(); // Math.random();
      fold[i] = (int) (i / indvCount) + 1; // make sure that each fold has each size sample
    }

    Sortor.quickSort(rdm, fold, 0, numRates - 1, true);

    int[] row_ptr = rateMatrix.getRowPointers();
    int[] col_idx = rateMatrix.getColumnIndices();

    int f = 0;
    for (int u = 0, um = rateMatrix.numRows(); u < um; u++) {
      for (int idx = row_ptr[u], end = row_ptr[u + 1]; idx < end; idx++) {
        int j = col_idx[idx];
        // if randomly put an int 1-5 to entry (u, j), we cannot make sure equal size for each fold
        assignMatrix.set(u, j, fold[f++]);
      }
    }
  }