Unsupervised Learning

Unsupervised learning is a type of machine learning in which only the input data is provided and the output data (labelling) is absent. Algorithms in unsupervised learning are left on their own without any assistance, to find results on their own and in this method of learning there are no correct or wrong answers.

Some of the popular unsupervised learning algorithms are:

• Hierarchical clustering: builds a multilevel hierarchy of clusters by creating a cluster tree

• k-Means clustering: partitions data into k distinct clusters based on distance to the centroid of a cluster

• Apriori algorithm: for association rule learning problems