What are clustering algorithms in machine learning?

What are clustering algorithms in machine learning?

Clustering algorithms are techniques used to group similar data points together based on their features.

Can you explain some common clustering algorithms?

Sure! Some common clustering algorithms include K-means, hierarchical clustering, and DBSCAN.

How does the K-means algorithm work?

K-means works by partitioning data into K clusters, where each data point belongs to the cluster with the nearest mean.

What are the advantages and disadvantages of using clustering?

Advantages include discovering patterns in data, while disadvantages can be sensitivity to outliers and the need to specify the number of clusters.