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)