Fastica sklearn

1. How does fastICA work?
2. What is the difference between PCA and ICA?
3. What is kurtosis in ICA?

How does fastICA work?

Like most ICA algorithms, FastICA seeks an orthogonal rotation of prewhitened data, through a fixed-point iteration scheme, that maximizes a measure of non-Gaussianity of the rotated components.

What is the difference between PCA and ICA?

PCA vs ICA

Specifically, PCA is often used to compress information i.e. dimensionality reduction. While ICA aims to separate information by transforming the input space into a maximally independent basis.

What is kurtosis in ICA?

ICA decomposes a multivariate signal into 'independent' components through 1. orthogonal rotation and 2. maximizing statistical independence between components in some way - one method used is to maximize non-gaussianity (kurtosis).