【发布时间】:2022-01-07 10:49:01
【问题描述】:
import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split, cross_val_score
from sklearn.linear_model import LinearRegression
boston = pd.read_csv('boston.csv')
x = boston.drop('medv', axis=1).values
y = boston['medv'].values
reg = LinearRegression()
cross_val_score(reg, x, y, cv=5)
reg.predict(x)
在上面的代码中,我计算了我的线性回归回归器的 5 折交叉验证分数。但是当我尝试使用predict() 方法时,我收到一条错误消息:
This LinearRegression instance is not fitted yet. Call 'fit' with
appropriate arguments before using this estimator.
我认为回归器在执行交叉验证时是合适的。
【问题讨论】:
标签: python machine-learning scikit-learn linear-regression cross-validation