README.md
In pws3141/clusterICA: Approximate Independent Component Anaylsis
clusterICA
clusterICA: clustering method for ICA
An implementation of Independent Component Analysis, using clustering and optimisation of random projections of the data. It combines ordering of random points on the projective space and clustering of ≈the best points using divisive k-means until some tolerance condition is met, with an optimisation step for each cluster. Each loading is found sequentially, and Householder rotations are used to make the current loading orthogonal to all previous ones.
Requires:
jvcoords: uses whiten function within Independent Component Analysis
pws3141/clusterICA documentation built on July 14, 2020, 5:04 a.m.
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clusterICA
clusterICA: clustering method for ICA
An implementation of Independent Component Analysis, using clustering and optimisation of random projections of the data. It combines ordering of random points on the projective space and clustering of ≈the best points using divisive k-means until some tolerance condition is met, with an optimisation step for each cluster. Each loading is found sequentially, and Householder rotations are used to make the current loading orthogonal to all previous ones.
Requires:
jvcoords: uses whiten function within Independent Component Analysis
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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