Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: On non-iterative training of a neural classifier   Recently an algorithm, was discovered, which separates points in n-dimension
by planes in such a manner that no two points are left un-separated by at least
one plane{[}1-3{]}. By using this new algorithm we show that there are two ways
of classification by a neural network, for a large dimension feature space,
both of which are non-iterative and deterministic. To demonstrate the power of
both these methods we apply them exhaustively to the classical pattern
recognition problem: The Fisher-Anderson's, IRIS flower data set and present
the results.
  It is expected these methods will now be widely used for the training of
neural networks for Deep Learning not only because of their non-iterative and
deterministic nature but also because of their efficiency and speed and will
supersede other classification methods which are iterative in nature and rely
on error minimization.

30
The categories of this paper are: q-alg
19
The categories of this paper are: eess
8
The categories of this paper are: hep-ex
24
The categories of this paper are: dg-ga
4
The categories of this paper are: cond-mat
35
The categories of this paper are: mtrl-th
15
The categories of this paper are: nucl-ex
3
The categories of this paper are: physics
2
The categories of this paper are: math
34
The categories of this paper are: chem-ph
14
The categories of this paper are: math-ph
6
The categories of this paper are: astro-ph
27
The categories of this paper are: comp-gas
5
The categories of this paper are: gr-qc
29
The categories of this paper are: funct-an
25
The categories of this paper are: patt-sol