python - predict() 缺少 1 个必需的位置参数：sklearn LinearRegression 中的“X”

Question

我正在尝试使用简单的线性回归来预测薪水。其中 X 是工作年限，y 是工资。

这是我的代码

# Importing the libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

# Importing the dataset
dataset = pd.read_csv('Salary_Data.csv')
X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, 1].values


# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 0)

# Fitting Simple Linear Regression to the Training Set
from sklearn.linear_model import LinearRegression
regressor = LinearRegression
regressor(X_train, y_train)

# Predicting the Test set results
Y_pred = regressor.predict(X_test)

这是我的错误

Y_pred = regressor.predict(X_test)
Traceback (most recent call last):

  File "<ipython-input-28-e33267d5ef4e>", line 1, in <module>
    Y_pred = regressor.predict(X_test)

TypeError: predict() missing 1 required positional argument: 'X'

我究竟做错了什么？我该如何解决这个问题/错误？

标签： pythonscikit-learn

Answer 1

# Fitting Simple Linear Regression to the Training Set
from sklearn.linear_model import LinearRegression
regressor = LinearRegression()  # <-- you need to instantiate the regressor like so 
regressor.fit(X_train, y_train) # <-- you need to call the fit method of the regressor

# Predicting the Test set results
Y_pred = regressor.predict(X_test)