我正在使用数据集来查看工资与大学GPA之间的关系。我正在使用sklearn线性回归模型。我认为这些系数应该是拦截和关闭的。相应功能的值。但该模型给出了单一的价值。sklearn线性回归系数具有单个值输出
from sklearn.cross_validation import train_test_split
from sklearn.linear_model import LinearRegression
# Use only one feature : CollegeGPA
labour_data_gpa = labour_data[['collegeGPA']]
# salary as a dependent variable
labour_data_salary = labour_data[['Salary']]
# Split the data into training/testing sets
gpa_train, gpa_test, salary_train, salary_test = train_test_split(labour_data_gpa, labour_data_salary)
# Create linear regression object
regression = LinearRegression()
# Train the model using the training sets (first parameter is x)
regression.fit(gpa_train, salary_train)
#coefficients
regression.coef_
The output is : Out[12]: array([[ 3235.66359637]])
感谢您的教程链接! – MaxU