I've been thinking a bit about feature selection and have problems
making up my mind when it comes to what sort of solutions makes most
sense to initally focus on. If people have an unlimited number of
nodes then complexity is no longer a big problem.
My guess is that people historically use nested subset ranking as the
complexity is log N rather than N of exhaustive search wrappers. My
guts tells me that the latter will produce a better result (given you
also do Bonferroni correction or so) but who has an unlimited number
of nodes?
The real question is hidden somewhere in between the lines and it
doesn't only apply to feature selection.
karl
- computational power assertion Karl Wettin
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