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Which of the following scenarios is best suited for K-means clustering?

Practice Questions

Q1
Which of the following scenarios is best suited for K-means clustering?
  1. Identifying customer segments based on purchasing behavior
  2. Classifying emails as spam or not spam
  3. Predicting house prices based on features
  4. Finding the optimal path in a navigation system

Questions & Step-by-Step Solutions

Which of the following scenarios is best suited for K-means clustering?
  • Step 1: Understand what K-means clustering is. It is a method used to group similar items together based on their features.
  • Step 2: Identify the type of data you have. In this case, we are looking at customer purchasing behavior.
  • Step 3: Determine if the data can be grouped. K-means works best when you can find clear groups or clusters in the data.
  • Step 4: Think about what you want to achieve. Here, we want to segment customers based on how similar their purchasing habits are.
  • Step 5: Conclude that K-means clustering is suitable because it can effectively group customers with similar purchasing behaviors.
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