func (f LinearFunction) Predict(x mat.MatrixRO) (float64, error) {
if x.Cols() != f.InputDims() {
return 0, fmt.Errorf("x has %d columns. Expected %d.", x.Cols(), f.InputDims())
}
value, err := x.Times(&f.Weights)
if f.AFunc != nil {
return f.AFunc.Eval(value.Get(0, 0)), err
} else {
return value.Get(0, 0), err
}
}
func (f LinearFunction) PredictM(x mat.MatrixRO) (mat.MatrixRO, error) {
if x.Cols() != f.InputDims() {
return nil, fmt.Errorf("x has %d columns. Expected %d.", x.Cols(), f.InputDims())
}
y, err := x.Times(&f.Weights)
if err != nil {
return nil, fmt.Errorf("Error predicting before applying activation function. %v", err)
}
var yprime mat.MatrixRO = nil
if f.AFunc != nil {
yprime = Apply(y, f.AFunc.Eval)
} else {
yprime = y
}
return yprime, nil
}
