Gaussian Radial Basis Function Neural Network with Correlation Based Feature Selection Applied to Medical Text Categorization
| dc.contributor.author | Akın ÖZÇİFT | |
| dc.date.accessioned | 2024-07-24T09:08:45Z | |
| dc.date.available | 2024-07-24T09:08:45Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | Text categorization is an important field for information processing systems. Particularly, medical textprocessing is a popular research area that makes use of classification algorithms and dimension reductionstrategies from machine learning field. In this study, we propose a three stage algorithm to automaticallycategorize medical text from OHSUMED corpus. In the proposed algorithm, we use Correlation BasedFeature Filtering on top of Radial Basis Function Neural Network. The algorithm for 12 sample datasetsproduces 0.890 in terms macro average F-measure. In this context, both Correlation based Feature Filteringas a feature elimination strategy and Radial Basis Function Neural Network as text categorization algorithmare promising methods. | |
| dc.identifier.DOI-ID | 10.18466/cbayarfbe.466908 | |
| dc.identifier.issn | 1305-130X | |
| dc.identifier.uri | http://akademikarsiv.cbu.edu.tr:4000/handle/123456789/21555 | |
| dc.language.iso | eng | |
| dc.title | Gaussian Radial Basis Function Neural Network with Correlation Based Feature Selection Applied to Medical Text Categorization | |
| dc.type | Araştırma Makalesi |