On the Financial Situation Analysis with KNN and Naive Bayes Classification Algorithms
Makaleler > Tam Makale · 2020
Yazarlar: Oğuzcan Uludağ, Arif GÜRSOY
Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi, Diğer Kurumların Hakemli Dergileri, Uluslararası, TR Dizin (Ulakbim), 2020, cilt 10, ss 2881-2888
DOI: 10.21597/jist.703004
Özet
Classification, a data mining technique, has been applied on the financial parameters used in the Altman Z-Score formulas for a certain number of selected firms in manufacturing industry. The Altman Z-Score is used to estimate a firm's financial difficulties. The Z-Score value shows whether the financial position of the firm is good, moderate or risky. In this study, KNN and Naive Bayes algorithms are used as classification methods. The Z-Score values of all firms are calculated and a certain number of data for all three types are selected and taught to the system as learning data. Algorithms are run on the financial parameters in the Z-Score formulas of companies not taught to the system. Over all data, The KNN and Naive Bayes algorithms achieve 84–88% and 75–86% success, respectively. This study, where data mining techniques are applied on a finance model and successful results are achieved, will contribute to the application of different technologies in many different analysis processes of the financial sector.