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
Schedule
| Data | # Data points | # Dimensions | # Target Dimensions | Dimensionality Reduction Method | Clustering Technique | Rand Index | NMI | Accuracy |
|---|---|---|---|---|---|---|---|---|
| MNIST | ||||||||
| Gisette | ||||||||
| Olivetti Faces |
