Method multiclass_probability

svm.go:1647–1705

(k int, r [][]float64, p []float64)

}

func (this *SVM) multiclass_probability(k int, r [][]float64, p []float64) {
	var t, j int
	iter := 0
	max_iter := math.Max(100, float64(k))
	Q := make([][]float64, k)
	for i := range Q {
		Q[i] = make([]float64, k)
	}
	Qp := make([]float64, k)
	var pQp float64
	eps := float64(0.005) / float64(k)

	for t = 0; t < k; t++ {
		p[t] = float64(1.0) / float64(k) // Valid if k = 1
		Q[t][t] = 0
		for j = 0; j < t; j++ {
			Q[t][t] += r[j][t] * r[j][t]
			Q[t][j] = Q[j][t]
		}
		for j = t + 1; j < k; j++ {
			Q[t][t] += r[j][t] * r[j][t]
			Q[t][j] = -r[j][t] * r[t][j]
		}
	}
	for iter = 0; iter < int(max_iter); iter++ {
		// stopping condition, recalculate QP,pQP for numerical accuracy
		pQp = 0
		for t = 0; t < k; t++ {
			Qp[t] = 0
			for j = 0; j < k; j++ {
				Qp[t] += Q[t][j] * p[j]
			}
			pQp += p[t] * Qp[t]
		}
		max_error := float64(0)
		for t = 0; t < k; t++ {
			error := math.Abs(Qp[t] - pQp)
			if error > max_error {
				max_error = error
			}
		}
		if max_error < eps {
			break
		}

		for t = 0; t < k; t++ {
			diff := (-Qp[t] + pQp) / Q[t][t]
			p[t] += diff
			pQp = (pQp + diff*(diff*Q[t][t]+2*Qp[t])) / (1 + diff) / (1 + diff)
			for j = 0; j < k; j++ {
				Qp[j] = (Qp[j] + diff*Q[t][j]) / (1 + diff)
				p[j] /= (1 + diff)
			}
		}
	}
	if iter >= int(max_iter) {
		log.Println("Exceeds max_iter in multiclass_prob")
	}