On 03/19/2017 03:47 PM, Thomas Evangelidis wrote:
Which of the following methods would you recommend to select good
features (<=50) from a set of 534 features in order to train a
MLPregressor? Please take into account that the datasets I use for
training are small.
http://scikit-learn.org/stable/modules/feature_selection.html
And please don't tell me to use a neural network that supports the
dropout or any other algorithm for feature elimination. This is not
applicable in my case because I want to know the best 50 features in
order to append them to other types of feature that I am confident
that are important.
You can always use forward or backward selection as implemented in
mlxtend if you're patient. As your dataset is small that might work.
However, it might be hard tricky to get the MLP to run consistently -
though maybe not...
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