Arrange the following steps in the correct sequence for applying an unsupervised learning technique such as K-means clustering to a data set:

(a) Randomly initialize cluster centroids

(b) Assign each data point to nearest cluster centroid

(c)Update the cluster centroids based on the mean of data points assigned to each cluster

(d) Specify the number of clusters (K) to partition the data into

(e) Repeat steps B and C until convergence criteria are met

1. A(d),(a),(b),(c),(e)
2. B(a),(b),(c),(d),(e)
3. C(c),(b),(a),(d),(e)
4. D(d),(c),(a),(b),(e)

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Show answer & explanation

Correct answer: A. (d),(a),(b),(c),(e)

Explanation

Choose K, initialize centroids, assign each point to its nearest centroid, recompute centroids as means, and repeat the last two steps until convergence.