An Integrated approach for fuzzy logistic regression

Year 2018, Volume 11, Issue 1, 42 - 54, 29.06.2018

Nimet Yapıcı PEHLİVAN Aynur ŞAHİN

Abstract

The aim of this study is to introduced an integrated fuzzy logistic regression approach to describe the relationship between crisp inputs and fuzzy binary output. For this reason, we integrated the fuzzy logistic regression methods proposed by Pourahmad et al. [17]  and Sohn et al. [24] to define a possibility measure for each case and then used the logarithmic transformation of possibilistic odds as fuzzy output observations. To estimate the parameters of the fuzzy logistic regression model, Diamond [5]’s Fuzzy Least Squares (FLS) approach is used. A numerical example is presented and obtained results are compared with classic logistic regression model.

Keywords

Fuzzy Logistic Regression, Possibilistic odds, Fuzzy Least Squares

Bulanık Lojistik Regresyon için Entegre Bir Yaklaşım

Abstract

Bu çalışmanın amacı, kesin girdiler ile bulanık ikili çıktı arasındaki ilişkiyi tanımlamak için birleştirilmiş bulanık lojistik regresyon yaklaşımını tanıtmaktır. Bu nedenle, her bir durum için bir olasılık ölçüsü tanımlamak ve daha sonra olabilirlik oranlarının logaritmik dönüşümünü bulanık çıktı gözlemleri olarak kullanmak amacıyla Pourahmad ve ark. [17]  ve Sohn ve ark. [24]tarafından önerilen bulanık lojistik regresyon yöntemleri entegre edilmiştir. Bulanık lojistik regresyon modelinin parametrelerini tahmin etmek için, Diamond [5]’ın Bulanık En Küçük Kareler (FLS) yaklaşımı kullanılmıştır. Sayısal bir örnek sunulmuş ve elde edilen sonuçlar klasik lojistik regresyon modeli ile karşılaştırılmıştır.

Keywords

Bulanık Lojistik Regresyon, Olabilirlik Oranları, Bulanık En Küçük Kareler

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