DR+Clustering

From ResearchWiki

Goal of the project: Understand the impact of dimensionality reduction methods on clustering. Try to uncover relationship between a dimensionality reduction method and a clustering technique of your choice (if there exists any).

High dimensions are "weird".

A mathematician and his best friend, an engineer, attend a public lecture on geometry in thirteen-dimensional space.

"How did you like it?" the mathematician wants to know after the talk.

"My head's spinning", the engineer confesses. "How can you develop any intuition for thirteen-dimensional space?"

"Well, it's not even difficult. All I do is visualize the situation in arbitrary N-dimensional space and then set N = 13."

And Clustering is "hard" (though Amit Daniely, Nati Linial, Michael Saks say its only hard when it does not matter!)

Data

MNIST Digits data:

Leader Board