题目
题目链接
协方差矩阵是一种描述两个随机变量之间关系的矩阵，其计算公式为：
\[cov(X, Y) = \frac{1}{n-1} \times \sum_{i=1}^{n} (x_i - \mu_x)(y_i - \mu_y)
\]
其中，\(X\) 和 \(Y\) 是两个随机变量，\(\mu_x\) 和 \(\mu_y\) 是 \(X\) 和 \(Y\) 的均值。
标准代码如下
def calculate_covariance_matrix(vectors):n_features = len(vectors)n_observations = len(vectors[0])covariance_matrix = [[0 for _ in range(n_features)] for _ in range(n_features)]means = [sum(feature) / n_observations for feature in vectors]for i in range(n_features):for j in range(i, n_features):covariance = sum((vectors[i][k] - means[i]) * (vectors[j][k] - means[j]) for k in range(n_observations)) / (n_observations - 1)covariance_matrix[i][j] = covariance_matrix[j][i] = covariancereturn covariance_matrix
