What Is Meant by Clustering of ICA (Independent Component Analysis) Components?

1. What does clustering mean in PCA?
2. What is cluster analysis and its steps?
3. Why do PCA before clustering?
4. Can tSNE be used for clustering?

What does clustering mean in PCA?

Cluster analysis or clustering is the assignment of a set of observations into subsets (called clusters) so that observations in the same cluster are similar in some sense.

What is cluster analysis and its steps?

Cluster Analysis is the process to find similar groups of objects in order to form clusters. It is an unsupervised machine learning-based algorithm that acts on unlabelled data. A group of data points would comprise together to form a cluster in which all the objects would belong to the same group.

Why do PCA before clustering?

By doing PCA you are retaining all the important information. If your data exhibits clustering, this will be generally revealed after your PCA analysis: by retaining only the components with the highest variance, the clusters will be likely more visibile (as they are most spread out).

Can tSNE be used for clustering?

tSNE, (t-distributed stochastic neighbor embedding) is a clustering technique that has a similar end result to PCA, (principal component analysis).