灰色关联法-优快云博客

本文链接：https://blog.youkuaiyun.com/NULLSET1/article/details/129818783

该代码读取Excel文件，使用pandas和numpy进行数据处理。定义了一个函数来计算灰关联系数，然后对特征列和目标列计算这些系数。系数计算完成后，按降序排序并用matplotlib进行条形图展示，以直观地比较各特征的相关性。

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import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
data = pd.read_excel('./final_parameter.xlsx')
y = data.iloc[:, -1]
def grey_relation_coefficient(x, y):
    x_mean = np.mean(x)
    y_mean = np.mean(y)
   
    numerator = np.sum((x - x_mean) * (y - y_mean))
    denominator = np.sqrt(np.sum((x - x_mean) ** 2) * np.sum((y - y_mean) ** 2))
    r = numerator / denominator
    if r > 0:
        delta = np.min(np.abs((x - y) / y))
        grey_relation_coefficient = (1 + delta * r) / 2
    elif r < 0:
        delta = np.min(np.abs((x - y) / y))
        grey_relation_coefficient = (1 - delta * r) / 2
    else:
        grey_relation_coefficient = 1
    return grey_relation_coefficient
X = data.iloc[:, :-1].values
n = X.shape[1]
coefficients = []
for i in range(n):
    coefficients.append(grey_relation_coefficient(X[:, i], y))

sorted_idx = np.argsort(coefficients)
sorted_coef = [coefficients[i] for i in sorted_idx]
sorted_names = [data.columns[i] for i in sorted_idx]

plt.figure(figsize=(8, 6))
plt.barh(range(n), sorted_coef, align='center', color='grey')
plt.yticks(range(n), sorted_names)
plt.xlabel('Grey Relation Coefficient')
plt.show()