EVALUATION OF ASSOCIATION RULES BASED ON CERTAINTY FACTOR:  AN APPLICATION ON DIABETES DATA SET

Mehmet KIVRAK; Faruk Berat AKÇEŞME; Cemil ÇOLAK

Makale detayları

EVALUATION OF ASSOCIATION RULES BASED ON CERTAINTY FACTOR: AN APPLICATION ON DIABETES DATA SET

Yazarlar:

Mehmet KIVRAK | Faruk Berat AKÇEŞME | Cemil ÇOLAK

Yayıncı:

İstanbul Technical University

Ana Başlıklar:

Uygulamalı fizik

Dergi:

The Journal of Cognitive Systems 2020 Vol.5 Issue 1, pp.19-22

Belge Tipi:

Makale

Yayın Tarihi:

6/2020

Belge Dili:

İngilizce

Document ID (Org No.):

2000664808

Sıklık:

İki Yıllık

pISSN:

2548-0650

Özet:

 

Data mining is the process of discovering useful information that has not been previously revealed from large amounts of data. Association rules mining is one of the most important techniques used in data mining and artificial intelligence. The first research in the association rules was to find relationships between different products in the customer transaction database and customer purchase models. Based on these relationships, researchers have begun to expand the field of data mining. One of these areas is the application of the rules of association in the field of medicine. Thus, through these applications, the relationship of various features in medical data can be discovered, and the findings obtained can aid medical diagnosis. Support and confidence are the two primary measures employed in the evaluation of association rules. The rules obtained with these two values are often correct ; however, they are not strong rules. For this reason, there are many interestingness measures proposed to achieve stronger rules. Most of the rules, especially with a high support value, are misleading. For this reason, there are many interestingness measures proposed to achieve stronger rules. This study aims to establish strong association rules with variables in the open-sourced diabetes data set. In the current study, the Apriori algorithm was used to obtain the rules. As a result of the analysis, only 52 confidence and support criteria were taken into consideration. For more powerful rules, certainty factor was used as one of the interestingness measures proposed in the literature, and it was concluded that only 39 of these rules were strong as a result of the analysis.

Makale detayları

EVALUATION OF ASSOCIATION RULES BASED ON CERTAINTY FACTOR: AN APPLICATION ON DIABETES DATA SET

Yazarlar: Mehmet KIVRAK | Faruk Berat AKÇEŞME | Cemil ÇOLAK

Yayıncı: İstanbul Technical University

Ana Başlıklar: Uygulamalı fizik

Dergi: The Journal of Cognitive Systems 2020 Vol.5 Issue 1, pp.19-22

Belge Tipi: Makale

Yayın Tarihi: 6/2020

Belge Dili: İngilizce

Document ID (Org No.): 2000664808

Sıklık: İki Yıllık

pISSN: 2548-0650

Sayı

Yazarlar:

Mehmet KIVRAK | Faruk Berat AKÇEŞME | Cemil ÇOLAK

Yayıncı:

İstanbul Technical University

Ana Başlıklar:

Uygulamalı fizik

Dergi:

The Journal of Cognitive Systems 2020 Vol.5 Issue 1, pp.19-22

Belge Tipi:

Makale

Yayın Tarihi:

6/2020

Belge Dili:

İngilizce

Document ID (Org No.):

2000664808

Sıklık:

İki Yıllık

pISSN:

2548-0650