Practice K-Nearest Neighbors (KNN) - 2.3 | Classification Algorithms | Data Science Basic
K12 Students

Academics

AI-Powered learning for Grades 8–12, aligned with major Indian and international curricula.

Academics
Professionals

Professional Courses

Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.

Professional Courses
Games

Interactive Games

Fun, engaging games to boost memory, math fluency, typing speed, and English skillsβ€”perfect for learners of all ages.

games

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does KNN stand for?

πŸ’‘ Hint: Recall the main term used in the algorithm.

Question 2

Easy

What is meant by majority voting in KNN?

πŸ’‘ Hint: Think about how votes are counted.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What does the K in KNN represent?

  • Number of classes
  • Number of neighbors
  • Total data points

πŸ’‘ Hint: Think about what the algorithm needs to decide the classes.

Question 2

True or False: KNN assumes a normal distribution of data.

  • True
  • False

πŸ’‘ Hint: Consider the flexibility of KNN in working with data.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You are given a dataset with features that are on different scales. How would you ensure KNN performs effectively on this data?

πŸ’‘ Hint: Consider how distance is measured in KNN.

Question 2

Define a scenario where KNN might not perform well, and explain why.

πŸ’‘ Hint: Think about how distance behaves in more than three dimensions.

Challenge and get performance evaluation