37 #ifndef SHARK_ALGORITHMS_MCSVMMMRTRAINER_H 38 #define SHARK_ALGORITHMS_MCSVMMMRTRAINER_H 94 template <
class InputType,
class CacheType =
float>
110 : base_type(kernel, C, offset, unconstrained)
115 {
return "McSvmMMRTrainer"; }
123 RealVector alpha(ic,0.0);
124 RealVector bias(classes,0.0);
125 RealMatrix gamma(classes, 1,1.0);
129 for (
unsigned int y=0; y<classes; y++)
133 QpFloatType mood = (
QpFloatType)(-1.0 / (
double)classes);
135 for (
unsigned int r=0, yv=0; yv<classes; yv++)
137 for (
unsigned int yw=0; yw<classes; yw++, r++)
140 if (yv == yw) M.
add(r, 0, val);
153 PrecomputedMatrixType matrix(&km);
177 for (std::size_t i=0; i<ic; i++)
179 unsigned int y = dataset.
element(i).label;
180 for (
unsigned int c=0; c<classes; c++)
195 template <
class InputType>
206 {
return "LinearMcSvmMMRTrainer"; }