Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multidimensional data classification with artificial neural networks   Multi-dimensional data classification is an important and challenging problem
in many astro-particle experiments. Neural networks have proved to be versatile
and robust in multi-dimensional data classification. In this article we shall
study the classification of gamma from the hadrons for the MAGIC Experiment.
Two neural networks have been used for the classification task. One is
Multi-Layer Perceptron based on supervised learning and other is
Self-Organising Map (SOM), which is based on unsupervised learning technique.
The results have been shown and the possible ways of combining these networks
have been proposed to yield better and faster classification results.

13
The categories of this paper are: quant-ph
30
The categories of this paper are: q-alg
31
The categories of this paper are: ao-sci
8
The categories of this paper are: hep-ex
11
The categories of this paper are: hep-lat
18
The categories of this paper are: econ
0
The categories of this paper are: hep-ph
26
The categories of this paper are: bayes-an
28
The categories of this paper are: alg-geom
33
The categories of this paper are: plasm-ph
22
The categories of this paper are: chao-dyn
7
The categories of this paper are: hep-th
9
The categories of this paper are: nlin
6
The categories of this paper are: astro-ph
17
The categories of this paper are: q-fin
35
The categories of this paper are: mtrl-th