18 return (z >= 0) ? log(1 + exp(-z)) : -z + log(1 + exp(z));
24 return -1 / (exp(z) + 1);
27 return -ez / (ez + 1);
33 return ez / (ez*(ez + 2) + 1);
44 return label*eta_t/((1+d)*norm);
46 x = eta_t + label*prediction + d;
53 float64_t W = x>=1. ? 0.86*x+0.01 : exp(0.8*x-0.65);
54 float64_t r = x>=1. ? x-log(W)-W : 0.2*x+0.65-W;
57 w = W*(1.+r/t*(u-r)/(u-2.*r))-x;
59 return -(label*w+prediction)/norm;
virtual float64_t get_update(float64_t prediction, float64_t label, float64_t eta_t, float64_t norm)
virtual float64_t first_derivative(float64_t z)
double norm(double *v, double p, int n)
virtual float64_t second_derivative(float64_t z)
all of classes and functions are contained in the shogun namespace
float64_t loss(float64_t z)
virtual float64_t get_square_grad(float64_t prediction, float64_t label)
virtual float64_t first_derivative(float64_t prediction, float64_t label)