Which of the following is NOT a step in the K-means clustering algorithm?
Practice Questions
1 question
Q1
Which of the following is NOT a step in the K-means clustering algorithm?
Assigning data points to the nearest centroid
Updating the centroid positions
Calculating the silhouette score
Choosing the initial centroids
Calculating the silhouette score is not a step in the K-means algorithm; it is an evaluation metric used after clustering.
Questions & Step-by-step Solutions
1 item
Q
Q: Which of the following is NOT a step in the K-means clustering algorithm?
Solution: Calculating the silhouette score is not a step in the K-means algorithm; it is an evaluation metric used after clustering.
Steps: 7
Step 1: Understand what K-means clustering is. It is a method used to group similar data points together into clusters.
Step 2: Identify the number of clusters (K) you want to create.
Step 3: Randomly select K initial centroids (the center points of the clusters).
Step 4: Assign each data point to the nearest centroid to form clusters.
Step 5: Recalculate the centroids by finding the average of all data points in each cluster.
Step 6: Repeat Steps 4 and 5 until the centroids no longer change significantly or a set number of iterations is reached.
Step 7: Understand that calculating the silhouette score is NOT part of the K-means algorithm; it is used later to evaluate how well the clustering has performed.
