An Evaluation of Classification Algorithms Using Mc Nemar's Test

Bostanci B., Bostanci E.

7th International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012), Madhya Pradesh, Hindistan, 14 - 16 Aralık 2012, cilt.201, ss.15-26 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 201
  • Doi Numarası: 10.1007/978-81-322-1038-2_2
  • Basıldığı Şehir: Madhya Pradesh
  • Basıldığı Ülke: Hindistan
  • Sayfa Sayıları: ss.15-26
  • Anahtar Kelimeler: Classifier Evaluation, Classification algorithms, Mc Nemar's test
  • Ankara Üniversitesi Adresli: Evet

Özet

Five classification algorithms namely J48, Naive Bayes, Multi layer Perceptron, IBK and Bayes Net are evaluated using Mc Nemar's test over datasets including both nominal and numeric attributes. It was found that Multi layer Perceptron performed better than the two other classification methods for both nominal and numerical datasets. Furthermore, it was observed that the results of our evaluation concur with Kappa statistic and Root Mean Squared Error, two well-known metrics used for evaluating machine learning algorithms.