Clustering is an Unsupervised Machine Learning technique. It involves identifying some pattern (size, color, and so on) in unlabeled data points for grouping them into clusters.

Also, given a set of data points, you can use a clustering algorithm to classify each data point into a specific group.

Each group is called a cluster which contains similar data points. They have minuscule or no similarity with the data points belonging to another cluster.

Rubiscape provides the following Clustering algorithms in Machine Learning –

• DBSCAN
• Centroid Based Clustering
• Distance Based Clustering
• Hierarchical Clustering
• Incremental Learning

Clustering algorithms find a wide range of applications a few of which are mentioned below.

• Anomaly Detection
• Social Media Analysis
• Recommendation Engines
• Segmentation in Markets