Nursery

Importpandasaspd
Importnumpyasnp
Fromsklearn.model_selectionimporttrain_test_split
Fromsklearn.linear_modelimportLinearRegression
#Loadthedataset
url=https://archive.ics.uci.edu/ml/machine-learning-databases/nursery/nursery.data
names=[‘parents’,‘has_nurs’,‘form’,‘children’,‘housing’,‘finance’,‘social’,‘health’,‘class’]
dataset=pd.read_csv(url,names=names)
#Identifyindependentandtargetvariables
X=dataset.drop(‘class’,axis=1)
Y=dataset[‘class’]
#Convertcategoricalvariablesintonumericalvariablesusingone-hotencoding
X=pd.get_dummies(X)
#Splitintotrainingandtestingsets
X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.2,random_state=42)
#Buildalinearregressionmodel
Model=LinearRegression()
Model.fit(X_train,y_train)
#Printthecoefficientsofthemodel
Print(“Intercept:“,model.intercept_)
Print(“Coefficients:“,model.coef_)
#Predictthetargetvariableforthetestingset
Y_pred=model.predict(X_test)
#EvaluatethemodelusingMeanSquaredError(MSE)
Mse=np.mean((y_test–y_pred)**2)
Print(“MSE:“,mse)