scikit-learn - 通过 SVR 执行 RFECV 时出错分类器未公开“coef_”或“feature_importances_”属性

Question

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn.linear_model import LinearRegression
from sklearn.feature_selection import RFECV
from sklearn.svm import SVR


housing = pd.read_csv('boston.csv')


x = housing.iloc[:, 0:13].values
y = housing.iloc[:, 13:14].values
y = np.ravel(y)


from sklearn.model_selection import train_test_split
x_train, x_test, y_train, y_test = train_test_split(x, y, test_size =   0.33, random_state = 0)
y_train = np.ravel(y_train)


regressor = SVR(kernel = 'poly', degree=2)
regressor.fit(x_train, y_train)

rfecv = RFECV(estimator = regressor, cv=5, scoring='accuracy')

执行上述行（即 rfecv）后，我收到以下错误：

“RuntimeError：分类器未公开“coef_”或“feature_importances_”属性”

我究竟做错了什么 ？？？

标签： scikit-learn

Answer 1

之后你需要安装它，将其更改为：

regressor = SVR(kernel = 'poly', degree=2)


rfecv = RFECV(estimator = regressor, cv=5, scoring='accuracy')
rfecv = rfec.fit(x_train, y_train)