Gaussian Radial Basis Function Neural Network with Correlation Based Feature Selection Applied to Medical Text Categorization
Abstract
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.
URI
https://app.trdizin.gov.tr/publication/paper/detail/TXpFNU5USTNOdz09http://hdl.handle.net/20.500.12481/3576
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