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| author | WeichenXu <WeichenXu123@outlook.com> | 2017-04-21 17:58:13 +0000 |
|---|---|---|
| committer | DB Tsai <dbtsai@dbtsai.com> | 2017-04-21 17:58:13 +0000 |
| commit | eb00378f0eed6afbf328ae6cd541cc202d14c1f0 (patch) | |
| tree | 97bc09893183aa42337458606f1431006dfcdba0 /R/pkg/R/functions.R | |
| parent | a750a595976791cb8a77063f690ea8f82ea75a8f (diff) | |
| download | spark-eb00378f0eed6afbf328ae6cd541cc202d14c1f0.tar.gz spark-eb00378f0eed6afbf328ae6cd541cc202d14c1f0.tar.bz2 spark-eb00378f0eed6afbf328ae6cd541cc202d14c1f0.zip | |
[SPARK-20423][ML] fix MLOR coeffs centering when reg == 0
## What changes were proposed in this pull request?
When reg == 0, MLOR has multiple solutions and we need to centralize the coeffs to get identical result.
BUT current implementation centralize the `coefficientMatrix` by the global coeffs means.
In fact the `coefficientMatrix` should be centralized on each feature index itself.
Because, according to the MLOR probability distribution function, it can be proven easily that:
suppose `{ w0, w1, .. w(K-1) }` make up the `coefficientMatrix`,
then `{ w0 + c, w1 + c, ... w(K - 1) + c}` will also be the equivalent solution.
`c` is an arbitrary vector of `numFeatures` dimension.
reference
https://core.ac.uk/download/pdf/6287975.pdf
So that we need to centralize the `coefficientMatrix` on each feature dimension separately.
**We can also confirm this through R library `glmnet`, that MLOR in `glmnet` always generate coefficients result that the sum of each dimension is all `zero`, when reg == 0.**
## How was this patch tested?
Tests added.
Author: WeichenXu <WeichenXu123@outlook.com>
Closes #17706 from WeichenXu123/mlor_center.
Diffstat (limited to 'R/pkg/R/functions.R')
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