Bünyamin DEMİR, Feyza GÜRBÜZ, İkbal ESKİ, Zeynel Abidin KUŞ

Meyve renk özelliklerini tahmin etmek için veri madenciliği yaklaşımı

Renk, birçok taze meyve ve sebzenin kalitesini ve tüketici tercihlerini belirleyen önemli bir özelliktir. Meyvelerin renk ölçümünde, uniform renk ölçeği nedeniyle CIE L*a*b* en çok kullanılan renk uzayıdır. Bu çalışmada elma çeşitlerinin renk özelliklerine ait ham veriler ilk aşamada test ve eğitim verileri olarak iki kısma ayrılmış, eğitim verileri üzerinde analizler yapılmış ve test verileri ise testlerde kullanılmıştır. Find laws algoritması uygulanarak elde edilen kurallar Color index (CI), hue angle (h*) and Chroma (C*) değerlerini tahmin etmek için kullanılmıştır. İkinci aşamada ise ham veriler cluster analizine tabi tutularak Strict ve Liberal seçenekleri ile sınıflandırılmıştır. Find laws algoritması her bir sınıfa tek tek uygulanıp, her bir CI, h*, C* parametreleri için elde edilen 7 farklı tahmin kuralı R2 değerlerine göre karşılaştırılarak en yüksek doğruluğa sahip kurallar tespit edilmiştir.

Anahtar Kelimeler:

Elma, hue açısı, Lab*, renk uzayı

Data mining aproach for prediction of fruit color properties

Color is an important feature that dictates the quality and consumer preferences of many fresh fruits and vegetables. In color measurement of fruits, the CIE L*a*b* color space is widely used since it is a uniform color scale. In this study, raw data for the color features of apple varieties were divided into two parts as test and train data in the first stage, analyses were performed on train data and tests were performed on test data. The rules obtained by applying the Find laws algorithm were used to estimate the color index (CI), hue angle (h *) and Chroma (C *) values. In the second stage, raw data were classified by Strict and Liberal options of cluster analysis. Find Laws algorithm was applied to each cluster and 7 different prediction rules were obtained for CI, h*and C* parameters. R2 values of the rules were compared and the rules with the most accurate outcomes were identified. :

Keywords:

Apple, hue angle, Lab*, color space,

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