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I start from Principal Component Analysis. PCA is finding the axes of maximal eccentricity within a multidimensional space -- where the space is the variables d
by clebio 11y ago
I start from Principal Component Analysis. PCA is finding the axes of maximal eccentricity within a multidimensional space -- where the space is the variables describing some data set.
This is taking that _sort_ of approach and running it thoroughly out. What are topological and differential properties of a sample space, what can we do with the geometrical forms within that space, given what we know about (diffeomorphic) mappings, etc.
- upquark 11y agoThe space here is the space of probability distributions (each point is a distribution), not the sample space. So, no real connection with PCA.