A fast feature selection approach based on extreme learning machine and coefficient of variation

TAĞLUK, Mehmet Emin; Ertuğrul, Ömer Faruk

A fast feature selection approach based on extreme learning machine and coefficient of variation

ÖMER FARUK ERTUĞRUL, (Batman Üniversitesi, Elektrik-Elektronik Mühendisliği Bölümü, Batman, Türkiye)

Mehmet Emin TAĞLUK (İnönü Üniversitesi, Mühendislik Fakültesi, Elekrik Elektronik Mühendisliği Bölümü, Malatya, Türkiye)

Turkish Journal of Electrical Engineering and Computer Sciences

2 0

Yıl: 2017 Cilt: 25 Sayı: 4 Sayfa Aralığı: 3409 - 3420 Metin Dili: İngilizce İndeks Tarihi: 29-07-2022

A fast feature selection approach based on extreme learning machine and coefficient of variation

Öz:

Feature selection is the method of reducing the size of data without degrading their accuracy. In this study, we propose a novel feature selection approach, based on extreme learning machines (ELMs) and the coefficient of variation (CV). In the proposed approach, the most relevant features are identified by ranking each feature with the coefficient obtained through ELM divided by CV. The achieved accuracies and computational costs, obtained with the use of features selected via the proposed approach in 9 classification and 26 regression benchmark data sets, were compared to those obtained with all features, as well as those obtained with the features selected by a wrapper and a filtering method. The achieved accuracy values obtained with the proposed approach were generally higher than when using all features. Furthermore, high feature reduction ratios were obtained with the proposed approach, including the achieved feature reduction ratios in epilepsy, liver, EMG, shuttle, and abalone. Stock data sets were 90.48%, 90%, 70.59%, 66.67%, 75%, and 77.78%, respectively. This approach is an extremely fast process that is independent of the employed machine-learning methods.

Anahtar Kelime:

Konular: Mühendislik, Elektrik ve Elektronik

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık

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APA	Ertuğrul Ö, TAĞLUK M (2017). A fast feature selection approach based on extreme learning machine and coefficient of variation. , 3409 - 3420.
Chicago	Ertuğrul Ömer Faruk,TAĞLUK Mehmet Emin A fast feature selection approach based on extreme learning machine and coefficient of variation. (2017): 3409 - 3420.
MLA	Ertuğrul Ömer Faruk,TAĞLUK Mehmet Emin A fast feature selection approach based on extreme learning machine and coefficient of variation. , 2017, ss.3409 - 3420.
AMA	Ertuğrul Ö,TAĞLUK M A fast feature selection approach based on extreme learning machine and coefficient of variation. . 2017; 3409 - 3420.
Vancouver	Ertuğrul Ö,TAĞLUK M A fast feature selection approach based on extreme learning machine and coefficient of variation. . 2017; 3409 - 3420.
IEEE	Ertuğrul Ö,TAĞLUK M "A fast feature selection approach based on extreme learning machine and coefficient of variation." , ss.3409 - 3420, 2017.
ISNAD	Ertuğrul, Ömer Faruk - TAĞLUK, Mehmet Emin. "A fast feature selection approach based on extreme learning machine and coefficient of variation". (2017), 3409-3420.

APA	Ertuğrul Ö, TAĞLUK M (2017). A fast feature selection approach based on extreme learning machine and coefficient of variation. Turkish Journal of Electrical Engineering and Computer Sciences, 25(4), 3409 - 3420.
Chicago	Ertuğrul Ömer Faruk,TAĞLUK Mehmet Emin A fast feature selection approach based on extreme learning machine and coefficient of variation. Turkish Journal of Electrical Engineering and Computer Sciences 25, no.4 (2017): 3409 - 3420.
MLA	Ertuğrul Ömer Faruk,TAĞLUK Mehmet Emin A fast feature selection approach based on extreme learning machine and coefficient of variation. Turkish Journal of Electrical Engineering and Computer Sciences, vol.25, no.4, 2017, ss.3409 - 3420.
AMA	Ertuğrul Ö,TAĞLUK M A fast feature selection approach based on extreme learning machine and coefficient of variation. Turkish Journal of Electrical Engineering and Computer Sciences. 2017; 25(4): 3409 - 3420.
Vancouver	Ertuğrul Ö,TAĞLUK M A fast feature selection approach based on extreme learning machine and coefficient of variation. Turkish Journal of Electrical Engineering and Computer Sciences. 2017; 25(4): 3409 - 3420.
IEEE	Ertuğrul Ö,TAĞLUK M "A fast feature selection approach based on extreme learning machine and coefficient of variation." Turkish Journal of Electrical Engineering and Computer Sciences, 25, ss.3409 - 3420, 2017.
ISNAD	Ertuğrul, Ömer Faruk - TAĞLUK, Mehmet Emin. "A fast feature selection approach based on extreme learning machine and coefficient of variation". Turkish Journal of Electrical Engineering and Computer Sciences 25/4 (2017), 3409-3420.