Add new stochastic decomposition code
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Key: MAHOUT-792
URL: https://issues.apache.org/jira/browse/MAHOUT-792
Project: Mahout
Issue Type: New Feature
Reporter: Ted Dunning
I have figured out some simplification for our SSVD algorithms. This
eliminates the QR decomposition and makes life easier.
I will produce a patch that contains the following:
- a CholeskyDecomposition implementation that does pivoting (and thus
rank-revealing) or not. This should actually be useful for solution of large
out-of-core least squares problems.
- an in-memory SSVD implementation that should work for matrices up to about
1/3 of available memory.
- an out-of-core SSVD threaded implementation that should work for very large
matrices. It should take time about equal to the cost of reading the input
matrix 4 times and will require working disk roughly equal to the size of the
input.
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