Comparison of Classification Algorithms Used Medical Documents Categorization

Autor:	Sahin, Durmus Ozkan, Kilic, Erdal
Rok vydání:	2018
Předmět:	Computer Science - Information Retrieval Computer Science - Computation and Language Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	Volume of text based documents have been increasing day by day. Medical documents are located within this growing text documents. In this study, the techniques used for text classification applied on medical documents and evaluated classification performance. Used data sets are multi class and multi labelled. Chi Square (CHI) technique was used for feature selection also SMO, NB, C4.5, RF and KNN algorithms was used for classification. The aim of this study, success of various classifiers is evaluated on multi class and multi label data sets consisting of medical documents. The first 400 features, while the most successful in the KNN classifier, feature number 400 and after the SMO has become the most successful classifier. Comment: International Conference on Computer Science and Engineering 2016
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1811.00869 Zobrazit plný text záznamu View this record from Arxiv