Python 3.7.6 机器学习中怎么保存和加载模型

1、使用 joblib

保存模型

import joblib
output_model_file = 'saved_model.pkl'
joblib.dump(linear_regressor, output_model_file)

加载模型，注释部分直接进行了预测

import joblib
model_file = 'saved_model.pkl'
linear_regressor = joblib.load(model_file)

# y_test_pred = linear_regressor.predict(X_test)

2、使用 pickle

保存模型

import pickle
output_model_file = 'saved_model.pkl'
with open(model_file, 'wb') as mf:
    pickle.dump(linear_regressor, mf)

加载模型，注释部分直接进行了预测

import pickle
model_file = 'saved_model.pkl'
with open(model_file, 'rb') as mf:
    linear_regressor = pickle.load(mf)

# y_test_pred = linear_regressor.predict(X_test)