Turkish Character Usage in Text Classification

Year 2021, Volume: 1 Issue: 1, 53 - 58, 30.08.2021

Ali Aycan Kolukısa

Abstract

This study is prepared to examine the effects of Turkish character usage on text data by using multiple classifiers. Regression Classifiers, SVM, NB-Classifiers, and ANN are frequently used in supervised learning
methods, especially in classification problems. Regression classifiers generally come in two types: as Linear and Logistic. There are also more than one type of Naive Bayes classifier. In our study, after mentioning the properties of Linear Regression and Logistic Regression classifiers in general terms, why Logistic Regression is much more suitable for this study is explained. Then, with the usage of "Logistic Regression", "LinearSVC", "MultinomialNB", "ComplementNB", "BernoulliNB" and "Perceptron" classifiers, the analyzing part starts. Our datasets consist of abstracts-parts from 64 Turkish articles, which have 4 different classes as Physical Sciences, Social Sciences, Educational Sciences, and Economics Administrative Sciences. The data files are all in CSV file format, however, two different data files were prepared. One with original Turkish characters, and the other with its English equivalent formation targeting the Turkish characters "Ç, ç, Ö, ö, Ü, ü, Ş, ş, İ, ı, ğ". In its English-like equivalent file, these were replaced with "C, c, O, o, U, u, S, s, I, i, g" respectively.

Keywords

Accuracy rate, bag of words, English characters, logistic regression, Turkish characters

References

• [1] S. Alp and E. Öz, Makine Öğrenmesinde Sınıflandırma Yöntemleri ve R Uygulamaları. Nobel Akademik Yayıncılık, 2019.
• [2] H.B. Akın and E. Şentürk, "Bireylerin Mutluluk Düzeylerinin Ordinal Lojistik Regresyon Analizi ile İncelenmesi", Öneri Dergisi, vol. 10, no. 37, 183-193, 2012.
• [3] S. Swaminatah, "Logistic Regression- Detailed Owerview. Towards Data Science." towardsdatascience.com, 2018 [Online]. Available: https://towardsdatascience.com/logistic-regression-detailed-overview-46c4da4303bc, 2018. [Accessed: Jan. 15, 2021]
• [4] Ö. Şahin, "iOS platformunda görme engelliler için TL tanıma uygulaması" Yüksek Lisans Tezi, T.C. Selçuk Üniversitesi, Fen Bilimleri Enstitüsü, Konya, 73, 2017.
• [5] B. Aleksey, "Linear and non-linear activation, and softmax." Kaggle.com, 2018 [Online]. Available:https://www.kaggle.com/residentmario/linear-and-non-linear-activation-and-softmax, 2018. [Accessed: Jan. 13, 20201]
• [6] F. Doğan and İ. Türkoğlu, "Derin Öğrenme Modelleri ve Uygulama Alanlarına İlişkin Bir Derleme", Dicle Üniversitesi Mühendislik Fakültesi DÜMF Dergisi, vol. 10, no. 2, 409-445, 2019.
• [7] G. Silahtaroğlu, Veri Madenciliği Yöntemleri. Papatya Yayıncılık, İstanbul, 2013.