On 05/15/2012 05:16 PM, Mathieu Blondel wrote:


On Tue, May 15, 2012 at 11:59 PM, David Warde-Farley <[email protected] <mailto:[email protected]>> wrote:


    I haven't had a look at these classes myself but I think working
    with raw
    NumPy arrays is a better idea in terms of efficiency.


Since it abstracts away the data representation, SequentialDataset is useful if you want to support both dense and sparse representations in your MLP implementation.
I am not sure if we want to support sparse data. I have no experience with using MLPs on sparse data. Could this be done efficiently? The weight vector would need to be represented explicitly and densely, I guess.

Any ideas?
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