scikit-learn: Decision Trees


Difficulty: 2 | Problem written by zeyad_omar

Educational Resource: https://towardsdatascience.com/a-beginners-guide-to-scikit-learn-14b7e51d71a4

Problem reported in interviews at


A decision tree classifier is a supervised learning technique that is used to classifiy the data based on some pivot points.

For example, if you can not decide whether to go outside or not so you ask your self "Is it rainy outside?", "Do i like playing football?", and "Will I enjoy my time with those I am going to play with?"

Based on the answers to the questions at each node of the decision tree, the classifier makes a decision (classification).

In this probelm you are required to use sklearn to implement the decision tree classifier.

Sample Input:
<class 'list'>
X_train: [[0, 0], [1, 1]]
<class 'list'>
y_train: [0, 1]
<class 'list'>
X_test: [[2, 2]]

Expected Output:
<class 'numpy.ndarray'>

This is a premium problem, to view more details of this problem please sign up for MLPro Premium. MLPro premium offers access to actual machine learning and data science interview questions and coding challenges commonly asked at tech companies all over the world

MLPro Premium also allows you to access all our high quality MCQs which are not available on the free tier.

Not able to solve a problem? MLPro premium brings you access to solutions for all problems available on MLPro

Get access to Premium only exclusive educational content available to only Premium users.

Have an issue, the MLPro support team is available 24X7 to Premium users.

This is a premium feature.
To access this and other such features, click on upgrade below.

Log in to post a comment


Input Test Case

Please enter only one test case at a time
numpy has been already imported as np (import numpy as np)