The aim of a cluster analysis is to group a set of objects in such a way that members of the same group (or cluster) are more similar to each other than to those in other groups. This is an unsupervised machine learning method, also known as data segmentation or class discovery.
This workshop will cover:
- clustering of both observations and variables
- dissimilarity measures appropriate for a variety of data types
- hierarchical clustering analysis
- k-means clustering analysis