Hi,
I have a couple of questions regarding feature selection;
1. What choices are there in incremental feature selection and
training algorithms? Ideally, combined training and feature selection.
2. I was playing around with IterativeReliefOnline and got a bit
confused. Lets say I have;
FeatureSelector = SensitivityBasedFeatureSelection(
IterativeReliefOnline(transformer=N.abs),
FixedNElementTailSelector(10000,
mode='select',tail='upper'),
enable_states = ['selected_ids'])
smap = FeatureSelector(dataset)
Is 'smap' now the values in 'dataset' applying the final set of
selected features on all samples?
The reason I ask is that, as far as I understand, the online version
of 'IterativeRelief' would get updated with one more sample at a time.
Can I access the feature selections from the previous states, when
only dataset[1:-k] "was available"?
Thanks a bunch for any help you can give me!
Cheers,
Patrik
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