Which clustering algorithm is best for identifying spherical clusters?

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Question: Which clustering algorithm is best for identifying spherical clusters?

Options:

Correct Answer: K-Means

Solution:

K-Means is effective for identifying spherical clusters due to its centroid-based approach.

Which clustering algorithm is best for identifying spherical clusters?

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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