Examples with structures._HDPThetaStar._Connection structures._HDPThetaStar._Connection used on opensource projects

Example 11 with structures._HDPThetaStar._Connection

use of structures._HDPThetaStar._Connection in project IR_Base by Linda-sunshine.

the class CLRWithMMB method addConnection.

// add the edge assignment to corresponding cluster
public void addConnection(_MMBAdaptStruct ui, _MMBAdaptStruct uj, int e) {
    _HDPThetaStar theta_g, theta_h;
    theta_g = ui.getOneNeighbor(uj).getHDPThetaStar();
    theta_h = uj.getOneNeighbor(ui).getHDPThetaStar();
    theta_g.addConnection(theta_h, e);
    theta_h.addConnection(theta_g, e);
}

Example 12 with structures._HDPThetaStar._Connection

use of structures._HDPThetaStar._Connection in project IR_Base by Linda-sunshine.

the class CLRWithMMB method saveClusterLanguageModels.

// Save the language models of thetaStars
public void saveClusterLanguageModels(String model) {
    PrintWriter writer;
    String filename;
    File dir = new File(model);
    _HDPThetaStar theta;
    double[] lm;
    try {
        if (!dir.exists())
            dir.mkdirs();
        for (int i = 0; i < m_kBar; i++) {
            theta = m_hdpThetaStars[i];
            filename = String.format("%s/%d.lm", model, theta.getIndex());
            writer = new PrintWriter(new File(filename));
            lm = theta.getLMStat();
            for (int v = 0; v < lm.length; v++) {
                if (v == lm.length - 1)
                    writer.write(Double.toString(lm[v]));
                else
                    writer.write(lm[v] + ",");
            }
            writer.close();
        }
    } catch (IOException e) {
        e.printStackTrace();
    }
}

Example 13 with structures._HDPThetaStar._Connection

use of structures._HDPThetaStar._Connection in project IR_Base by Linda-sunshine.

the class CLRWithMMB method rmConnection.

// remove the connection between ui and uj, where i->j \in g, j->i \in h.
public void rmConnection(_MMBAdaptStruct ui, _MMBAdaptStruct uj, int e) {
    _HDPThetaStar theta_g, theta_h;
    theta_g = ui.getOneNeighbor(uj).getHDPThetaStar();
    theta_h = uj.getOneNeighbor(ui).getHDPThetaStar();
    theta_g.rmConnection(theta_h, e);
    theta_h.rmConnection(theta_g, e);
}

Example 14 with structures._HDPThetaStar._Connection

use of structures._HDPThetaStar._Connection in project IR_Base by Linda-sunshine.

the class CLinAdaptWithMMB method loadUsers.

@Override
public void loadUsers(ArrayList<_User> userList) {
    m_userList = new ArrayList<_AdaptStruct>();
    // Init each user.
    for (_User user : userList) {
        m_userList.add(new _MMBAdaptStruct(user, m_dim));
    }
    m_pWeights = new double[m_gWeights.length];
    m_indicator = new _HDPThetaStar[m_userList.size()][m_userList.size()];
}

Example 15 with structures._HDPThetaStar._Connection

use of structures._HDPThetaStar._Connection in project IR_Base by Linda-sunshine.

the class MTCLinAdaptWithMMB method gradientByFunc.

@Override
protected void gradientByFunc(_AdaptStruct u, _Doc review, double weight, double[] g) {
    _Review r = (_Review) review;
    _HDPThetaStar theta = r.getHDPThetaStar();
    // feature index
    int n, k, s;
    int cIndex = theta.getIndex();
    if (cIndex < 0 || cIndex >= m_kBar)
        System.err.println("Error,cannot find the theta star!");
    int offset = m_dim * 2 * cIndex, offsetSup = m_dim * 2 * m_kBar;
    double[] Au = theta.getModel();
    double delta = (review.getYLabel() - logit(review.getSparse(), r)) * weight;
    // Bias term for individual user.
    // a[0] = ws0*x0; x0=1
    g[offset] -= delta * getSupWeights(0);
    // b[0]
    g[offset + m_dim] -= delta;
    // Bias term for super user.
    // a_s[0] = a_i0*w_g0*x_d0
    g[offsetSup] -= delta * Au[0] * m_gWeights[0];
    // b_s[0] = a_i0*x_d0
    g[offsetSup + m_dimSup] -= delta * Au[0];
    // Traverse all the feature dimension to calculate the gradient for both individual users and super user.
    for (_SparseFeature fv : review.getSparse()) {
        n = fv.getIndex() + 1;
        k = m_featureGroupMap[n];
        // w_si*x_di
        g[offset + k] -= delta * getSupWeights(n) * fv.getValue();
        // x_di
        g[offset + m_dim + k] -= delta * fv.getValue();
        s = m_featureGroupMap4SupUsr[n];
        // a_i*w_gi*x_di
        g[offsetSup + s] -= delta * Au[k] * m_gWeights[n] * fv.getValue();
        // a_i*x_di
        g[offsetSup + m_dimSup + s] -= delta * Au[k] * fv.getValue();
    }
}