[SciPy-Dev] Comparison of PLS algorithms
Fri Mar 4 10:39:27 CST 2011
Whoops, just realized, this should have gone to scikits-learn. My mistake.
Sorry about that,
On Fri, Mar 4, 2011 at 11:34 AM, Aman Thakral <email@example.com>wrote:
> Hi all,
> I've provided a summary of the features between the two PLS libraries
> submitted. Please see the table below:
> *Duchesnay* *Aman* *Inner Loop* Both NIPALS and CCA NIPALS only *Mean
> Centering* Yes Yes *Scaling to Unit Variance* Yes Yes *SVD alternative*
> Yes No *Deflation of Y* Using either X or Y scores X scores Only *Rotations
> (W* matrix)* Both X and Y X only *Raises exceptions for improper sizing
> of input matrices* Yes No *Provide Statistics (SPE, Hotelling's T)* No
> Yes *Provide Statistical limits* No Yes *Provide Variable importance to
> Projection (VIP)
> * No Yes
> In terms of performance, they should be same since the equations (for the
> parts that are found in both) are identical and both use numpy arrays to do
> calculations. I think the best course of action would be to use Duchesnay's
> code for the base, then add the missing parts from my code (statistics,
> statistical limits, VIP) to help users in their analysis. I will also get
> some examples together that uses duchesnay's code with some of the
> visualization functions to help users get a better understanding of PLS.
> Also, I was thinking about incorporating some inline weave for the NIPALS
> inner loop to improve the performance. I haven't used it before, so I'll
> have figure out the inner workings of weave first.
> Please let me know what you think.
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