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Which clustering algorithm is best for identifying spherical clusters?

Practice Questions

Q1
Which clustering algorithm is best for identifying spherical clusters?
  1. DBSCAN
  2. Agglomerative Clustering
  3. K-Means
  4. Gaussian Mixture Models

Questions & Step-by-Step Solutions

Which clustering algorithm is best for identifying spherical clusters?
  • Step 1: Understand what clustering means. Clustering is a way to group similar items together.
  • Step 2: Learn about spherical clusters. Spherical clusters are groups of data points that form a round shape.
  • Step 3: Know what K-Means is. K-Means is a clustering algorithm that groups data by finding the center (centroid) of clusters.
  • Step 4: Realize how K-Means works. K-Means assigns data points to the nearest centroid and then updates the centroid based on the assigned points.
  • Step 5: Understand why K-Means is good for spherical clusters. Since K-Means uses centroids, it effectively finds round-shaped groups of data.
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