Hi everybody!
David, it's your project, I'm just trying to help along ;)
About 2): Afaik there is nothing in sklearn at the moment
that can deal with missing variables and I feel the MLP
is one of the estimators where dealing with missing values
is hardest.
@David: I wouldn't keep you from trying but it seems a bit
out of the scope of the MLP. I think the idea for missing data
was to provide an additional mask as input that says
which values are missing. Dealing with this is much more natural
in naive Bayes or tree based methods than in the MLP I think.
@Vandana: For dealing with missing data, one easy way is to
set the missing variables to their mean over the dataset.
Usually for MLPs the input should be zero mean, unit variance.
So the missing variable would be just set to 0.
Do you know of any better way of dealing with missing values
in MLPs?
Cheers,
Andy
On 06/05/2012 07:51 PM, David Marek wrote:
I think you sent this mail only to me, please send all mails to
mailling list. Btw. Andreas is my mentor, so he is the one in charge
here :-)
Ad 1) Afaik all you need is one hidden layer, it's certainly possible
to add the possibility, but I think we decided that it's not a priority.
Ad 2) Good idea
David
---------- Forwarded message ----------
From: *Vandana Bachani* <vandana....@gmail.com
<mailto:vandana....@gmail.com>>
Date: Tue, Jun 5, 2012 at 6:59 PM
Subject: Re: [Scikit-learn-general] Contributing to scikit-learn
To: h4wk...@gmail.com <mailto:h4wk...@gmail.com>
Hi David,
I think we can add the following also to the to do list:
1. Any number of hidden layers and hidden units should be supported.
2. Missing data should be handled (several UCI datasets have missing
data).
I will look at the code and then send you a mail about my thoughts on
the same.
If you would like to have a look at my project report, I am attaching
the same.
Thanks,
Vandana
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