Unsupervised learning

Unsupervised learning deals with unlabeled data. The objective is to observe structure in data and find patterns. Tasks like cluster analysis, association rule mining, outlier detection, dimensionality reduction, and so on can be modeled as unsupervised learning problems. As the tasks involved in unsupervised learning vary vastly, there is no single process outline that we can follow. We will follow the process of some of the most common unsupervised learning problems.

Cluster analysis

Cluster analysis is a subset of unsupervised learning that aims to create groups of similar items from a set of items. Real life examples could be clustering movies according to various attributes like genre, length, ratings, and so on. Cluster ...

Get Learning Apache Mahout now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.