func (rbm *RBM) logistic(v *util.Vector, index int, isRow bool) (output float64) {
output = 0.0
if isRow {
output = util.VecDotProduct(v, rbm.lock.weights.GetValues(index))
} else {
for i := 0; i < rbm.lock.weights.NumLabels(); i++ {
output += v.Get(i) * rbm.lock.weights.Get(i, index)
}
}
output = 1.0 / (1 + math.Exp(-output))
return
}
// 计算 z = 1 + sum(exp(sum(w_i * x_i)))
//
// 在temp中保存 exp(sum(w_i * x_i))
func ComputeZ(weights *util.Matrix, features *util.Vector, label int, temp *util.Matrix) float64 {
result := float64(1.0)
numLabels := weights.NumLabels() + 1
for iLabel := 1; iLabel < numLabels; iLabel++ {
exp := math.Exp(util.VecDotProduct(features, weights.GetValues(iLabel-1)))
result += exp
tempVec := temp.GetValues(iLabel - 1)
if tempVec.IsSparse() {
for _, k := range features.Keys() {
tempVec.Set(k, exp)
}
} else {
tempVec.SetAll(exp)
}
}
return result
}