Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Atom Search Optimization with Simulated Annealing -- a Hybrid
  Metaheuristic Approach for Feature Selection   'Hybrid meta-heuristics' is one of the most interesting recent trends in the
field of optimization and feature selection (FS). In this paper, we have
proposed a binary variant of Atom Search Optimization (ASO) and its hybrid with
Simulated Annealing called ASO-SA techniques for FS. In order to map the real
values used by ASO to the binary domain of FS, we have used two different
transfer functions: S-shaped and V-shaped. We have hybridized this technique
with a local search technique called, SA We have applied the proposed feature
selection methods on 25 datasets from 4 different categories: UCI, Handwritten
digit recognition, Text, non-text separation, and Facial emotion recognition.
We have used 3 different classifiers (K-Nearest Neighbor, Multi-Layer
Perceptron and Random Forest) for evaluating the strength of the selected
featured by the binary ASO, ASO-SA and compared the results with some recent
wrapper-based algorithms. The experimental results confirm the superiority of
the proposed method both in terms of classification accuracy and number of
selected features.

35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
8
The categories of this paper are: hep-ex
0
The categories of this paper are: hep-ph
27
The categories of this paper are: comp-gas
33
The categories of this paper are: plasm-ph
12
The categories of this paper are: nucl-th
19
The categories of this paper are: eess
22
The categories of this paper are: chao-dyn
21
The categories of this paper are: adap-org
30
The categories of this paper are: q-alg
4
The categories of this paper are: cond-mat
34
The categories of this paper are: chem-ph
6
The categories of this paper are: astro-ph
31
The categories of this paper are: ao-sci
10
The categories of this paper are: q-bio