6.1.2.1 - K-Means Clustering
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Practice Questions
Test your understanding with targeted questions
What is a centroid in K-Means Clustering?
💡 Hint: Think about what it means to be 'central' or 'average'.
What does WCSS stand for?
💡 Hint: It’s a measure of how compact the clusters are.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What is the main objective of K-Means Clustering?
💡 Hint: Focus on what K-Means is designed to achieve!
True or False: K-Means Clustering does not require the number of clusters (K) to be predefined.
💡 Hint: Remember our class discussions on K’s importance.
1 more question available
Challenge Problems
Push your limits with advanced challenges
You are given a dataset with 2-dimensional data arranged in a circular pattern. Discuss how K-Means might struggle with such a dataset and propose alternative clustering methods.
💡 Hint: Think about the limitations of K-Means for various cluster shapes.
Consider a dataset with significant outliers and a desired number of K as 3. Propose a preprocessing step to improve K-Means performance on this data.
💡 Hint: Think about preprocessing techniques that can handle skewed data.
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