Examples with structures._thetaStar structures._thetaStar used on opensource projects

Example 1 with structures._thetaStar

use of structures._thetaStar in project IR_Base by Linda-sunshine.

the class CLRWithDP method calculateClusterProbPerUser.

// After we finish estimating the clusters, we calculate the probability of each user belongs to each cluster.
protected void calculateClusterProbPerUser() {
    double prob;
    _DPAdaptStruct user;
    double[] probs = new double[m_kBar];
    _thetaStar oldTheta;
    for (int i = 0; i < m_userList.size(); i++) {
        user = (_DPAdaptStruct) m_userList.get(i);
        if (user.getTestSize() == 0)
            continue;
        oldTheta = user.getThetaStar();
        for (int k = 0; k < m_kBar; k++) {
            user.setThetaStar(m_thetaStars[k]);
            // this proportion includes the user's current cluster assignment
            prob = calcLogLikelihood(user) + Math.log(m_thetaStars[k].getMemSize());
            // this will be in real space!
            probs[k] = Math.exp(prob);
        }
        Utils.L1Normalization(probs);
        user.setClusterPosterior(probs);
        // restore the cluster assignment during EM iterations
        user.setThetaStar(oldTheta);
    }
}

Example 2 with structures._thetaStar

use of structures._thetaStar in project IR_Base by Linda-sunshine.

the class CLRWithDP method predict.

public int predict(_AdaptStruct user, _thetaStar theta) {
    double[] As;
    double sum;
    int m, n, predL = 0, count = 0;
    for (_Review r : user.getReviews()) {
        if (r.getType() == rType.TEST) {
            As = theta.getModel();
            // Bias term: w_s0*a0+b0.
            sum = As[0] * MTCLinAdaptWithDP.m_supWeights[0] + As[m_dim];
            for (_SparseFeature fv : r.getSparse()) {
                n = fv.getIndex() + 1;
                m = m_featureGroupMap[n];
                sum += (As[m] * MTCLinAdaptWithDP.m_supWeights[n] + As[m_dim + m]) * fv.getValue();
            }
            if (sum > 0.5)
                predL = 1;
            if (predL == r.getYLabel())
                count++;
        }
    }
    return count;
}

Example 3 with structures._thetaStar

use of structures._thetaStar in project IR_Base by Linda-sunshine.

the class CLRWithDP method printTopWords.

void printTopWords(_thetaStar cluster) {
    MyPriorityQueue<_RankItem> wordRanker = new MyPriorityQueue<_RankItem>(10);
    double[] phi = cluster.getModel();
    // we will skip the bias term!
    System.out.format("Cluster %d (%d)\n[positive]: ", cluster.getIndex(), cluster.getMemSize());
    for (int i = 1; i < phi.length; i++) // top positive words with expected polarity
    wordRanker.add(new _RankItem(i, phi[i]));
    for (_RankItem it : wordRanker) System.out.format("%s:%.3f\t", m_features[it.m_index], phi[it.m_index]);
    System.out.format("\n[negative]: ");
    wordRanker.clear();
    for (int i = 1; i < phi.length; i++) // top negative words
    wordRanker.add(new _RankItem(i, -phi[i]));
    for (_RankItem it : wordRanker) System.out.format("%s:%.3f\t", m_features[it.m_index], phi[it.m_index]);
}

Example 4 with structures._thetaStar

use of structures._thetaStar in project IR_Base by Linda-sunshine.

the class CLRWithDP method calculate_E_step.

// The main MCMC algorithm, assign each user to clusters.
protected void calculate_E_step() {
    _thetaStar curThetaStar;
    _DPAdaptStruct user;
    for (int i = 0; i < m_userList.size(); i++) {
        user = (_DPAdaptStruct) m_userList.get(i);
        if (user.getAdaptationSize() == 0)
            continue;
        curThetaStar = user.getThetaStar();
        curThetaStar.updateMemCount(-1);
        if (curThetaStar.getMemSize() == 0) {
            // No data associated with the cluster.
            // move it back to \theta*
            swapTheta(m_kBar - 1, findThetaStar(curThetaStar));
            m_kBar--;
        }
        sampleOneInstance(user);
    }
}

Example 5 with structures._thetaStar

use of structures._thetaStar in project IR_Base by Linda-sunshine.

the class MTCLinAdaptWithDP method writeNorms.

public void writeNorms(String supFile, String clusterFile, int k) {
    ArrayList<_thetaStar> thetas = new ArrayList<_thetaStar>();
    for (int i = 0; i < m_kBar; i++) thetas.add(m_thetaStars[i]);
    Collections.sort(thetas);
    PrintWriter writer;
    double[] Ac;
    int size = m_supModels.size();
    ArrayList<double[]> Acs;
    double[] wc = new double[m_featureSize + 1];
    try {
        for (int i = 0; i < k; i++) {
            writer = new PrintWriter(new File(clusterFile + "_" + i));
            if (thetas.get(i).getAllModels().size() != size)
                continue;
            Acs = thetas.get(i).getAllModels();
            for (int j = 0; j < Acs.size(); j++) {
                Ac = Acs.get(j);
                wc = mapCluster(Ac, j);
                for (double w : wc) writer.write(w + ",");
                writer.write("\n");
            }
            writer.close();
        }
        writer = new PrintWriter(new File(supFile));
        for (double[] ws : m_supModels) {
            for (double w : ws) writer.write(w + ",");
            writer.write("\n");
        }
        writer.close();
    } catch (IOException e) {
        e.printStackTrace();
    }
}