Unsupervised learning is a type of machine learning algorithm used for grouping related data objects and finding hidden patterns by inferencing from unlabeled datasets—that is, training sets consisting of input data without labels.
Let's see a real-life example. Suppose you have a large collection of non-pirated and totally legal MP3 files in a crowded and massive folder on your hard drive. Now, what if you could build a predictive model that helps you automatically group together similar songs and organize them into your favorite categories, such as country, rap, and rock?
This is an act of assigning an item to a group so that an MP3 is added to the respective playlist in an unsupervised way. For classification, ...
