📅  最后修改于: 2023-12-03 15:00:49.910000             🧑  作者: Mango
这段Python代码可以用于获取线性回归模型的各个特征系数。在本例中,代码通过循环遍历X_train的每个列名,依次获取回归模型中的各个系数。最终,代码会打印每个特征的系数值。
代码中的 enumerate()
函数可以将一个可遍历的数据对象组合为一个索引序列,同时列出数据和数据下标,一般用在 for 循环中。
format()
函数用于将传入的参数进行字符串格式化。
line11的regression_model.coef_
是线性回归模型的系数,是一个二维数组,第一个维度表示模型的个数,第二个维度表示特征的个数。因为在这里只有一个模型,数量为1,所以使用regression_model.coef_[0]取出系数的数组。
返回类型是 markdown 的文本格式
for idx, col_name in enumerate(X_train.columns):
print("The coefficient for {} is {}".format(col_name, regression_model.coef_[0][idx]))
The coefficient for age is -0.012469350713788234
The coefficient for sex_female is 8.762584065506855
The coefficient for sex_male is -8.762584065506853
The coefficient for bmi is 0.3807106266997645
The coefficient for children_0 is -0.06605803000190659
The coefficient for children_1 is -0.946643170369065
The coefficient for children_2 is 0.2108032984623088
The coefficient for children_3 is 0.8800441822437507
The coefficient for children_4 is -0.35114697863423206
The coefficient for children_5 is -0.727399301642389
The coefficient for smoker_no is -16.907467151888124
The coefficient for smoker_yes is 16.907467151888128
The coefficient for region_northeast is 0.29321109056761263
The coefficient for region_northwest is 0.12145285638370737
The coefficient for region_southeast is -0.15412187246409794
The coefficient for region_southwest is -0.2605410744872277