
nak.liblinear.L2R_L2_SvcFunction Maven / Gradle / Ivy
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package nak.liblinear;
class L2R_L2_SvcFunction implements Function {
protected final Problem prob;
protected final double[] C;
protected final int[] I;
protected final double[] z;
protected int sizeI;
public L2R_L2_SvcFunction( Problem prob, double[] C ) {
int l = prob.l;
this.prob = prob;
z = new double[l];
I = new int[l];
this.C = C;
}
public double fun(double[] w) {
int i;
double f = 0;
double[] y = prob.y;
int l = prob.l;
int w_size = get_nr_variable();
Xv(w, z);
for (i = 0; i < w_size; i++)
f += w[i] * w[i];
f /= 2.0;
for (i = 0; i < l; i++) {
z[i] = y[i] * z[i];
double d = 1 - z[i];
if (d > 0) f += C[i] * d * d;
}
return (f);
}
public int get_nr_variable() {
return prob.n;
}
public void grad(double[] w, double[] g) {
double[] y = prob.y;
int l = prob.l;
int w_size = get_nr_variable();
sizeI = 0;
for (int i = 0; i < l; i++) {
if (z[i] < 1) {
z[sizeI] = C[i] * y[i] * (z[i] - 1);
I[sizeI] = i;
sizeI++;
}
}
subXTv(z, g);
for (int i = 0; i < w_size; i++)
g[i] = w[i] + 2 * g[i];
}
public void Hv(double[] s, double[] Hs) {
int i;
int w_size = get_nr_variable();
double[] wa = new double[sizeI];
subXv(s, wa);
for (i = 0; i < sizeI; i++)
wa[i] = C[I[i]] * wa[i];
subXTv(wa, Hs);
for (i = 0; i < w_size; i++)
Hs[i] = s[i] + 2 * Hs[i];
}
protected void subXTv(double[] v, double[] XTv) {
int i;
int w_size = get_nr_variable();
for (i = 0; i < w_size; i++)
XTv[i] = 0;
for (i = 0; i < sizeI; i++) {
for (Feature s : prob.x[I[i]]) {
XTv[s.getIndex() - 1] += v[i] * s.getValue();
}
}
}
private void subXv(double[] v, double[] Xv) {
for (int i = 0; i < sizeI; i++) {
Xv[i] = 0;
for (Feature s : prob.x[I[i]]) {
Xv[i] += v[s.getIndex() - 1] * s.getValue();
}
}
}
protected void Xv(double[] v, double[] Xv) {
for (int i = 0; i < prob.l; i++) {
Xv[i] = 0;
for (Feature s : prob.x[i]) {
Xv[i] += v[s.getIndex() - 1] * s.getValue();
}
}
}
}
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