K-means Clustering for Data Points

K-means clustering is a simple and effective way to cluster data points into two groups. This method is especially useful when the data set is not linearly separable.


Given a set of data points, cluster them into two groups using K-means clustering.


by robertrhee
The optimal solution for this problem is to use K-means clustering with two clusters. This is because the data points can be easily divided into two groups using this method. K-means clustering is also a simple and efficient algorithm that can be used to find the clusters in the data.

A.I. Evaluation of the Solution

The candidate's solution is correct and demonstrates a good understanding of the problem. The candidate has correctly identified that K-means clustering is the best algorithm to use for this problem and has correctly identified that two clusters are required.

Evaluated at: 2022-11-06 00:16:14