I'm trying to use the grey wolf optimization (GWO) for texts clustering. I used this code, https://github.com/7ossam81/EvoloPy-NN/blob/master/selector.py

I tried using the dimension 30 for the GWO as recommended by the author.. I also tried using a dimension which is equal to the number of feature.. but didn't work. My dataset has a shape of (2700, 18226). .. When I used the recommended formula in the file above ^^ ,, but I got a dimension of more than 600,000,000 which takes for ever......

Can any guide me?

  • $\begingroup$ Hi Mashael. This question may be off-topic here, because it is about debugging source code. Here we focus on theoretical and philosophical aspects. Try to ask this question on Data Science SE or Stack Overflow. $\endgroup$ – nbro Oct 29 '19 at 19:13
  • $\begingroup$ The first step is to reduce the amount of dimension downto only 2 which is boolean logic. In the second step the semantic aspect should be ignored because the ontology which is needed for creating the recommendation system isn't described in the existing literature very well. $\endgroup$ – Manuel Rodriguez Oct 30 '19 at 15:51
  • $\begingroup$ Apologies. Closed as out-of-scope. (Please check out our topics page.) $\endgroup$ – DukeZhou Oct 31 '19 at 15:24