Bayesci ağ yapısının öğrenilmesinde grafiksel bir yaklaşım

Year 2017, Volume 10, Issue 1, 1 - 10, 25.06.2017

Yasemin Kayhan ATILGAN Derya ERSEL

Abstract

Bu çalışmada, uzman bilgisi olmadığında Bayesci ağ yapısının öğrenilmesinde, çok boyutlu veri kümesindeki değişkenler arasındaki ilişki yapısını ortaya koyan Robust Coplot [1] grafiğinden yararlanılması önerilmiştir. Böylece, zaman alıcı öğrenme algoritmalarına gerek kalmadan Bayesci ağın oluşturulması sağlanmıştır. Önerilen yöntem bir veri kümesi üzerinde uygulanarak sonuçlar tartışılmış ve Robust Coplot grafiği ile veri kümesinin ön incelemesinin uzman bilgisi eksikliğini büyük ölçüde giderdiği gösterilmiştir.

Keywords

Bayesci ağlar, Bayesci ağlarda öğrenme, Robust Coplot.

A Graphical approach to learning Bayesian networks

Abstract

In this study, it is proposed to use Robust Coplot [1] that reveals the relationship structure between variables in multi-dimensional dataset to learn Bayesian network structure in the absence of expert knowledge. Hence, it is provided to create Bayesian networks without the need for time-consuming learning algorithms. The proposed method is applied to a data set and the results are discussed. Besides, it is shown that preliminary examination of data set with Robust Coplot provides to fulfill the deficiency of expert knowledge to a large extent

Keywords

Bayesian networks, learning Bayesian Networks, Robust Coplot.

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