bayes_regression_model(Python)

最新推荐文章于 2024-06-18 10:41:03 发布

BKevin101

最新推荐文章于 2024-06-18 10:41:03 发布

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文章标签： machine learning bayesRidge

本文链接：https://blog.youkuaiyun.com/qinlan1994/article/details/82291601

本文通过使用贝叶斯岭回归模型对波士顿房价数据集进行训练和预测，实现了房价的预测任务。采用80%的数据作为训练集，剩余20%作为测试集评估模型效果。结果显示，训练集和测试集的均方误差分别为[具体数值]和[具体数值]。

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import numpy as np
import pandas as pd
from sklearn import datasets
from sklearn.model_selection import train_test_split
from sklearn.linear_model import BayesianRidge
from sklearn.metrics import mean_squared_error

dataset = datasets.load_boston()
featurenames = list(dataset.feature_names)
x,y = dataset.data,dataset.target

x_train,x_test,y_train,y_test = train_test_split(x,y,test_size=0.2,random_state=1)

clf = BayesianRidge(n_iter=300,alpha_1=1.e-6,alpha_2=1.e-6)
clf.fit(x_train,y_train)
predict_train = clf.predict(x_train)
predict_test = clf.predict(x_test)
train_mse = mean_squared_error(y_train,predict_train)
test_mse = mean_squared_error(y_test,predict_test)
print('Train MSE = ',train_mse,' Test MSE = ',test_mse)