A FEATURE SELECTION APPLICATION FOR CLASSIFICATION: A BANKING APPLICATION

Öz

Operational data is gradually increasing with the effect of technological developments. Due to the increase in the amount and diversity of data, many difficulties are faced in data analysis and the evaluation of its results. Since the data transferred to the analysis stage consists of both relevant and irrelevant variables, time and resources required for analysis increases. It is obvious that resources and time are always limited. The aim of this study is to increase the success of classification methods under the limitation of time and resources by applying various feature selection methods. Feature selection methods were used on a set of banking customer data in order to determine the appropriate subsets for classification. Then, a classification method was applied on these selected subsets of features. By comparing the classification results, the contribution of the feature selection methods to the classification success was measured.

Anahtar Kelimeler

• Data Mining
• Classification
• Feature Selection
• Correlation Based Feature Selection
• Heuristic Search

SINIFLANDIRMA AMAÇLI DEĞİŞKEN ALT KÜMESİ SEÇİMİ: BİR BANKACILIK UYGULAMASI

Öz

Teknolojik gelişmelerin etkisi ile kaydedilen operasyonel veriler giderek artmaktadır. Veri miktarı ve çeşitliliğindeki artış nedeni ile analiz aşamasında ve analiz sonuçlarının değerlendirilmesi aşamasında birçok zorluk yaşanmaktadır. İlgili ve ilgisiz birçok verinin analiz aşamasına aktarılmasının sonucunda analizlerin yapılabilmesi için gerekli zaman ve kaynak gereksinimleri artmaktadır. Kaynakların ve zamanın daima sınırlı olacağı aşikardır. Bu çalışmanın amacı, bankacılık müşteri verileri üzerinde sınıflandırma amaçlı değişken seçimi uygulamaları yaparak ilgisiz değişkenleri elemek ve sınıflandırma çalışmasına katkıda bulunmaktır. Farklı değişken seçimi yöntemleri kullanılarak seçilen değişken alt kümeleri üzerinde sınıflandırma uygulaması yapılmıştır. Sınıflandırma sonuçları karşılaştırılarak değişken seçim yöntemlerinin başarısı ölçülmüştür.

Anahtar Kelimeler

• Veri Madenciliği
• Sınıflandırma
• Değişken Seçimi
• Korelasyon Bazlı Değişken Seçimi
• Sezgisel Arama.
• Data Mining
• Classification
• Feature Selection
• Correlation Based Feature Selection
• Heuristic Search

Kaynakça

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