Question : The question has 2 task, the 1 task i have completed and now I am stuck in 2 task.

- the 2 task question is mention below:

• Import required module fromsklearn.tree.
• Build a Decision tree Regressor model fromX_trainset andY_trainlabels, with default parameters. Name the model asdt_reg.
• Evaluate the model accuracy on training data set and print it's score.
• Evaluate the model accuracy on testing data set and print it's score.
• Predict the housing price for first two samples ofX_testset and print them.(Hint : Use predict() function)

The program which I have written is mentioned below which is wrong kindly correct me

import sklearn.datasets as datasets

from sklearn.model_selection import train_test_split

from sklearn.datasets import load_boston

import sklearn.model_selection as model_selection

from sklearn.tree import DecisionTreeRegressor

from sklearn import metrics

import pandas as pd

import numpy as np

# task 1

np.random.seed(100)

boston = datasets.load_boston()

X_train, X_test, Y_train, Y_test = model_selection.train_test_split(boston.data, boston.target,random_state = 30)

print(X_train.shape)

print(X_test.shape)

#task 2

dt_reg = DecisionTreeRegressor()

dt_reg = dt_reg.fit(X_train, Y_train)

print('Accuracy of Train Data :', dt_reg.score(X_train,Y_train))

print('Accuracy of Test Data :', dt_reg.score(X_test,Y_test))

y_pred = dt_reg.predict(X_test)

print(y_pred[0:2])