Which of the following statements is true about K-means clustering?
Correct Answer: K-means is sensitive to the initial placement of centroids.
- Step 1: Understand what K-means clustering is. It is a method used to group data points into clusters based on their similarities.
- Step 2: Learn about centroids. In K-means, a centroid is the center point of a cluster.
- Step 3: Know that K-means starts by randomly placing centroids in the data space.
- Step 4: Realize that the initial placement of these centroids can lead to different clustering results.
- Step 5: Understand that if the centroids are placed poorly, the algorithm may not find the best clusters.
- Step 6: Conclude that K-means is sensitive to where the centroids start, which can affect the final outcome of the clustering.
No concepts available.
