Question

Which option correctly orders the steps of k-means clustering? 1. Re-cluster the data points 2. Choose k random observations to calculate each cluster's mean 3. Update centroid to take cluster mean 4. Repeat until centroids are constant 5. Calculate data point distance to centroids o 2,3,4,5,1 o 2,5,3,1,4 o 3,5,1,4,2 o 2,1,4,5,3

Answer 1

The correct order of the steps in k-means clustering is: 1. Choose k random observations to calculate each cluster mean 2. Calculate data point distance to centroids, 3. Update centroid to take cluster mean, 4. Re-cluster the data points, 5. Repeat until centroids are constant.

Step-by-step explanation:

1. The correct order of the steps in k-means clustering is:
2. Choose k random observations to calculate each cluster's mean
3. Calculate data point distance to centroids
4. Update centroid to take cluster mean
5. Re-cluster the data points
6. Repeat until centroids are constant

For example, let's say we have a dataset of 100 data points and we want to cluster them into 3 groups. We start by randomly selecting 3 observations from the dataset and calculating their means. Then, we assign each data point to the cluster with the closest mean. After that, we calculate the distances between each data point and the centroids, update the centroids to take the mean of each cluster, re-cluster the data points based on the updated centroids, and repeat the process until the centroids no longer change.

Answer 2

The correct order of the steps in k-means clustering is: 2, 5, 3, 1, 4.

Step-by-step explanation:

1. Choose k random observations to calculate each cluster's mean
2. Calculate the data point distance to centroids
3. Update centroid to take cluster mean
4. Re-cluster the data points
5. Repeat until centroids are constant