我需要编写一个函数以获取数据集的曲线拟合。下面的代码是我所拥有的。它尝试使用梯度下降来找到最适合数据的多项式系数。

//solves for y using the form y = a + bx + cx^2 ...
double calc_polynomial(int degree, double x, double* coeffs) {
    double y = 0;

    for (int i = 0; i <= degree; i++)
        y += coeffs[i] * pow(x, i);

    return y;
}

//find polynomial fit
//returns an array of coefficients degree + 1 long
double* poly_fit(double* x, double* y, int count, int degree, double learningRate, int iterations) {
    double* coeffs = malloc(sizeof(double) * (degree + 1));
    double* sums = malloc(sizeof(double) * (degree + 1));

    for (int i = 0; i <= degree; i++)
        coeffs[i] = 0;

    for (int i = 0; i < iterations; i++) {
        //reset sums each iteration
        for (int j = 0; j <= degree; j++)
            sums[j] = 0;

        //update weights
        for (int j = 0; j < count; j++) {
            double error = calc_polynomial(degree, x[j], coeffs) - y[j];

            //update sums
            for (int k = 0; k <= degree; k++)
                sums[k] += error * pow(x[j], k);
        }

        //subtract sums
        for (int j = 0; j <= degree; j++)
            coeffs[j] -= sums[j] * learningRate;
    }

    free(sums);

    return coeffs;
}

而我的测试代码：

double x[] = { 0, 1, 2, 3, 4 };
double y[] = { 5, 3, 2, 3, 5 };
int size = sizeof(x) / sizeof(*x);

int degree = 1;
double* coeffs = poly_fit(x, y, size, degree, 0.01, 1000);

for (int i = 0; i <= degree; i++)
    printf("%lf\n", coeffs[i]);

上面的代码在度= 1时起作用，但是更高的值会导致系数以nan的形式返回。

我也尝试过更换

coeffs[j] -= sums[j] * learningRate;

和

coeffs[j] -= (1/count) * sums[j] * learningRate;

但是我回到0而不是nan。

有人知道我在做什么错吗？