I am a bit confused with the Harmony search for feature selection. Hopefully the expertise here can kindly help to answer my queries.
Where should I fit the data set into theHarmony search? Can I say that in Harmony Memory (in step 2 initialise Harmony Memory) that the features are randomly selected from a dataset? How exactly is Harmony Memory the complete dataset?
My understanding is that each row in Harmony Memory = feature subset, hence each decision variable in Harmony Memory represents a feature. So for the case of multi-dimensional datasets that have a few samples with various features (for example : Gene Expression data), how can Harmony Memory be formed?
If you work with harmony search, you should maybe know about the fact that harmony search is in fact a special case of evolution strategies and that some results reported by the "inventor" of harmony search, Z.W. Geem, seem extremely unlikely: http://www.dennisweyland.net/blog/?p=12
I would like to recommend you the following article: I may be helpful to you..
Mahamad Nabab Alam, Biswarup Das, Vinay Pant, A comparative study of metaheuristic optimization approaches for directional overcurrent relays coordination, Electric Power Systems Research, Volume 128, November 2015, Pages 39-52, ISSN 0378-7796, http://dx.doi.org/10.1016/j.epsr.2015.06.018.
(http://www.sciencedirect.com/science/article/pii/S0378779615001947)
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