Which distance metric is commonly used in K-means clustering?
Correct Answer: Euclidean distance
- Step 1: Understand that K-means clustering is a method used to group similar data points together.
- Step 2: Know that in K-means, we need to measure how far apart the data points are from the center of their group, called a centroid.
- Step 3: The distance between data points and centroids is measured using a formula.
- Step 4: The most common formula used for this measurement is called Euclidean distance.
- Step 5: Euclidean distance calculates the straight-line distance between two points in space.
No concepts available.
