public void reset(FeatureVector wv) {
this.iter = 0;
Arrays.fill(dir, 0);
Arrays.fill(this.steepestDescDir, 0);
Arrays.fill(w, 0);
Arrays.fill(newW, 0);
Arrays.fill(grad, 0);
Arrays.fill(newGrad, 0);
for (int i = 0; i < wv.size(); ++i) {
int fid = wv.idByIndex(i);
double v = wv.valueByIndex(i);
w[fid - 1] = v;
}
lossFunction.eval(w, grad);
Arrays.fill(alphas, 0);
this.sList.clear();
this.yList.clear();
this.roList.clear();
this.prevVals.clear();
this.value = evalL1();
}
/**
* eval loss + L1 reg
*
* @return
*/
protected double evalL1() {
double val = lossFunction.eval(newW, newGrad);
if (DEBUG || verbose) {
stderr.println("loss:" + val);
}
if (C > 0) {
for (int i = 1; i < dim; ++i) {
val += Math.abs(newW[i]) * C;
}
}
return val;
}
public void init() {
stderr.println(this.getClass().getName() + "#init()");
this.iter = 0;
this.alphas = new double[m];
this.dir = new double[dim + 1];
this.steepestDescDir = new double[dim + 1];
this.grad = new double[dim + 1];
this.w = new double[dim + 1];
this.newGrad = new double[dim + 1];
this.newW = new double[dim + 1];
lossFunction.eval(this.w, this.grad);
this.sList = new Stack<double[]>();
this.yList = new Stack<double[]>();
this.roList = new Stack<Double>();
this.value = evalL1();
this.prevVals = new Stack<Double>();
}
