A new intelligent classifier for breast cancer diagnosis based on a rough set and extreme learning machine: RS + ELM

Yılmaz KAYA

Makale detayları

A new intelligent classifier for breast cancer diagnosis based on a rough set and extreme learning machine: RS + ELM

Yazarlar:

Yılmaz KAYA

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2013 Vol.21 Issue Sup.1, pp.2079-2091

Belge Tipi:

Makale

Yayın Tarihi:

11/2012

Belge Dili:

Türkçe

Document ID (Org No.):

2000743492

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632

Özet:

 

Breast cancer is one of the leading causes of death among women all around  the world. Therefore, true and early diagnosis of breast cancer is an  important problem. The rough set (RS) and extreme learning machine (ELM)  methods were used collectively in this study for the diagnosis of breast  cancer. The unnecessary attributes were discarded from the dataset by means  of the RS approach. The classification process by means of ELM was performed  using the remaining attributes. The Wisconsin Breast Cancer dataset (WBCD),  derived from the University of California Irvine machine learning database,  was used for the purpose of testing the proposed hybrid model and the  success rate of the RS + ELM model was determined as 100%. Moreover,  the most appropriate attributes for the diagnosis of breast cancer were  determined from the WBCD in this study. It is considered that the proposed  method will be useful in similar medical practices.

 

Breast cancer is one of the leading causes of death among women all around  the world. Therefore, true and early diagnosis of breast cancer is an  important problem. The rough set (RS) and extreme learning machine (ELM)  methods were used collectively in this study for the diagnosis of breast  cancer. The unnecessary attributes were discarded from the dataset by means  of the RS approach. The classification process by means of ELM was performed  using the remaining attributes. The Wisconsin Breast Cancer dataset (WBCD),  derived from the University of California Irvine machine learning database,  was used for the purpose of testing the proposed hybrid model and the  success rate of the RS + ELM model was determined as 100%. Moreover,  the most appropriate attributes for the diagnosis of breast cancer were  determined from the WBCD in this study. It is considered that the proposed  method will be useful in similar medical practices.

Makale detayları

A new intelligent classifier for breast cancer diagnosis based on a rough set and extreme learning machine: RS + ELM

Yazarlar: Yılmaz KAYA

Yayıncı: TUBITAK

Dergi: Turkish Journal of Electrical Engineering and Computer Science 2013 Vol.21 Issue Sup.1, pp.2079-2091

Belge Tipi: Makale

Yayın Tarihi: 11/2012

Belge Dili: Türkçe

Document ID (Org No.): 2000743492

Sıklık: İki Aylık

eISSN: 1303-6203

pISSN: 1300-0632

Sayı

Yazarlar:

Yılmaz KAYA

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2013 Vol.21 Issue Sup.1, pp.2079-2091

Belge Tipi:

Makale

Yayın Tarihi:

11/2012

Belge Dili:

Türkçe

Document ID (Org No.):

2000743492

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632