题解 | 使用正规方程的线性回归

import numpy as np


def linear_regression_normal_equation(
    X: list[list[float]], y: list[float]
) -> list[float]:
    # 实现代码
    X_transpose = X.T
    # 计算正规方程的解
    theta = np.linalg.inv(X_transpose.dot(X)).dot(X_transpose).dot(y)
    theta = np.round(theta, 4).flatten().tolist()
    return theta


if __name__ == "__main__":
    import ast

    x = np.array(ast.literal_eval(input()))
    y = np.array(ast.literal_eval(input())).reshape(-1, 1)

    # Perform linear regression
    coefficients = linear_regression_normal_equation(x, y)

    # Print the coefficients
    print(coefficients)