Gaussian Radial Basis Function Neural Network with Correlation Based Feature Selection Applied to Medical Text Categorization

Yıl 2019, , 75 - 80, 22.03.2019

Akın Özçift

https://doi.org/10.18466/cbayarfbe.466908

Öz

Text categorization is an important field for information processing
systems. Particularly, medical text processing is a popular research area that
makes use of classification algorithms and dimension reduction strategies from
machine learning field. In this study, we propose a three stage algorithm to
automatically categorize medical text from OHSUMED corpus. In the proposed
algorithm, we use Correlation Based Feature Filtering on top of Radial Basis
Function Neural Network. The algorithm for 12 sample datasets produces 0.890 in
terms macro average F-measure. In this context, both Correlation based Feature
Filtering as a feature elimination strategy and Radial Basis Function Neural
Network as text categorization algorithm are promising methods

Anahtar Kelimeler

Machine learning, text categorization, neural networks, feature selection

Kaynakça

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