Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Cost effective approach on feature selection using genetic algorithms
  and fuzzy logic for diabetes diagnosis   A way to enhance the performance of a model that combines genetic algorithms
and fuzzy logic for feature selection and classification is proposed. Early
diagnosis of any disease with less cost is preferable. Diabetes is one such
disease. Diabetes has become the fourth leading cause of death in developed
countries and there is substantial evidence that it is reaching epidemic
proportions in many developing and newly industrialized nations. In medical
diagnosis, patterns consist of observable symptoms along with the results of
diagnostic tests. These tests have various associated costs and risks. In the
automated design of pattern classification, the proposed system solves the
feature subset selection problem. It is a task of identifying and selecting a
useful subset of pattern-representing features from a larger set of features.
Using fuzzy rule-based classification system, the proposed system proves to
improve the classification accuracy.

14
The categories of this paper are: math-ph
8
The categories of this paper are: hep-ex
32
The categories of this paper are: atom-ph
0
The categories of this paper are: hep-ph
16
The categories of this paper are: stat
24
The categories of this paper are: dg-ga
20
The categories of this paper are: acc-phys
27
The categories of this paper are: comp-gas
35
The categories of this paper are: mtrl-th
23
The categories of this paper are: solv-int
28
The categories of this paper are: alg-geom
30
The categories of this paper are: q-alg
9
The categories of this paper are: nlin
17
The categories of this paper are: q-fin
10
The categories of this paper are: q-bio
36
The categories of this paper are: cmp-lg