十一、模型的保存和加载
1.sklearn模型的保存和加载api
- from sklearn.externals import joblib
- 保存:joblib.dump(estimator,‘test.pkl’)
- 加载:estimator = joblib.load(‘test.pkl’)
2.线性回归的模型保存和加载案例
def load_dump_demo():
'''
模型保存和加载
'''
data = load_boston()
x_train, x_test, y_train, y_test = train_test_split(data.data, data.target, random_state=22)
transfer = StandardScaler()
x_train = transfer.fit_transform(x_train)
x_test = transfer.fit_transform(x_test)
estimator = joblib.load("test.pkl")
y_predict = estimator.predict(x_test)
print("预测值为:\n", y_predict)
print("模型中的系数为:\n", estimator.coef_)
print("模型中的偏置为:\n", estimator.intercept_)
error = mean_squared_error(y_test,y_predict)
=print("误差为:",error)