func OptimizeWeights(init_weights []float64, all_labels [][]float64) []float64 {
log.Printf("optimize ...\n")
var solver optimization.Solver
if *solver_name == "gradient" {
solver = &optimization.GradientDescentSolver{}
}
if *solver_name == "conjugate" {
solver = &optimization.GradientDescentSolver{}
}
if solver == nil {
solver = &optimization.LmBFGSSolver{}
}
solver.Init(map[string]interface{}{
"MaxIter": *max_iter,
"LogFunc": func(level int, message string) {
log.Printf("solver[level=%v]:%v", level, message)
},
})
problem := &optimization.Problem{
ValueAndGradientFunc: func(p optimization.Point) (float64, optimization.Point) { return opt_func_grad(p, all_labels) },
}
m, v := solver.Solve(problem, optimization.VectorDensePoint(init_weights))
log.Printf("solver min value %v #f=%v #g=%v at %v\n", v, problem.NumValue, problem.NumGradient, m.String())
weights := optimization.VectorToDense(m)
normalize(weights)
return weights
}
func test_solver(p optimization.Point, name string, solver optimization.Solver) {
log.Printf("solver %s ...\n", name)
solver.Init(map[string]interface{}{
"MaxIter": 48,
"LogFunc": func(level int, message string) {
log.Print(message)
},
})
problem := &optimization.Problem{
ValueFunc: opt_func,
GradientFunc: opt_grad,
}
m, y := solver.Solve(problem, p)
log.Printf("solver %s min value %v at %v #f=%v #g=%v\n", name, y, m.String(), problem.NumValue, problem.NumGradient)
}
func test_solver(A, b []float64, p optimization.Point, name string, solver optimization.Solver) {
log.Printf("solver %s ...\n", name)
solver.Init(map[string]interface{}{
"MaxIter": *max_iter,
"LogFunc": func(level int, message string) {
log.Printf(message)
},
})
problem := &optimization.Problem{
ValueFunc: func(p optimization.Point) float64 { return opt_func(A, b, p) },
GradientFunc: func(p optimization.Point) optimization.Point { return opt_grad(A, b, p) },
}
m, v := solver.Solve(problem, p)
log.Printf("solver %s min value %v #f=%v #g=%v at %v\n", name, v, problem.NumValue, problem.NumGradient, m.String())
}