局部加权线性回归代码

以下是Python实现局部加权线性回归的代码：

import numpy as np

def kernel(point, xmat, k):
    m, n = np.shape(xmat)
    weights = np.mat(np.eye(m))
    for j in range(m):
        diff = point - X[j]
        weights[j, j] = np.exp(diff * diff.T / (-2.0 * k ** 2))
    return weights

def localWeight(point, xmat, ymat, k):
    wei = kernel(point, xmat, k)
    W = (X.T * (wei * X)).I * (X.T * wei * ymat.T)
    return W

def localWeightRegression(xmat, ymat, k):
    m, n = np.shape(xmat)
    ypred = np.zeros(m)
    for i in range(m):
        ypred[i] = xmat[i] * localWeight(xmat[i], xmat, ymat, k)
    return ypred

其中，`kernel()`函数用于计算权重矩阵，`localWeight()`函数用于计算回归系数，`localWeightRegression()`函数用于进行预测。