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What type of data is K-means clustering best suited for?

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Question: What type of data is K-means clustering best suited for?

Options:

  1. Categorical data
  2. Numerical data
  3. Text data
  4. Time series data

Correct Answer: Numerical data

Solution: 

K-means clustering is best suited for numerical data, as it relies on calculating distances between data points.

What type of data is K-means clustering best suited for?

Practice Questions

Q1
What type of data is K-means clustering best suited for?
  1. Categorical data
  2. Numerical data
  3. Text data
  4. Time series data

Questions & Step-by-Step Solutions

What type of data is K-means clustering best suited for?
Correct Answer: Numerical data
  • Step 1: Understand what K-means clustering is. It is a method used to group similar data points together.
  • Step 2: Know that K-means clustering works by finding the center of groups (clusters) of data points.
  • Step 3: Realize that to find these centers, K-means needs to calculate distances between data points.
  • Step 4: Recognize that distances can be easily calculated for numerical data (like height, weight, or temperature).
  • Step 5: Conclude that K-means clustering is best suited for numerical data because it relies on these distance calculations.
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