import numpy as np
from sklearn.linear_model import Ridge
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_squared_error
 
x=np.array([[1,2],[2,3],[3,1],[4,3],[5,3]])
y=np.array([5,6,8,9,11])
 
x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.2,random_state=42)
 
model=Ridge(alpha=0.5)
model.fit(x_train,y_train)
 
y_pred=model.predict(x_test)
 
accuracy=np.sqrt(mean_squared_error(y_test,y_pred))
print("Accuracy:",accuracy)

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