What is the primary goal of clustering algorithms like K-Means?

To maximize the margin between classes
To minimize prediction errors
To group similar data points
To visualize data relationships

The primary goal of clustering algorithms like K-Means is to group similar data points together. This can be done by finding the centroids of each cluster and then assigning each data point to the cluster with the closest centroid. K-Means is a simple and effective clustering algorithm that is often used in machine learning and data mining.

Option A is incorrect because the goal of clustering algorithms is not to maximize the margin between classes. The goal is to group similar data points together.

Option B is incorrect because the goal of clustering algorithms is not to minimize prediction errors. The goal is to group similar data points together.

Option C is correct because the goal of clustering algorithms is to group similar data points together.

Option D is incorrect because the goal of clustering algorithms is not to visualize data relationships. The goal is to group similar data points together.