Practice Lab: Implementing And Evaluating Logistic Regression And Knn, Interpreting Confusion Matrices (6)
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Lab: Implementing and Evaluating Logistic Regression and KNN, Interpreting Confusion Matrices

Practice - Lab: Implementing and Evaluating Logistic Regression and KNN, Interpreting Confusion Matrices

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the primary objective of Logistic Regression?

💡 Hint: Think about its name and what it's often used for.

Question 2 Easy

What does K in KNN stand for?

💡 Hint: Related to how many 'neighbors' we look at.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does Logistic Regression predict?

Continuous values
Binary outcomes
Categorical values

💡 Hint: Think about its use case in classification.

Question 2

True or False: KNN builds a model during training.

True
False

💡 Hint: Consider the definition of 'training' in predictive modeling.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

You have a dataset with a severe class imbalance. Describe the steps you would take to prepare the data and choose evaluation metrics.

💡 Hint: Consider the implications of using accuracy alone.

Challenge 2 Hard

Given that KNN is sensitive to irrelevant features, explain how you'd assess feature relevance before applying KNN.

💡 Hint: Think about what constitutes a 'noisy' feature.

Get performance evaluation

Reference links

Supplementary resources to enhance your learning experience.