Incremental construction of rule ensembles using classifiers produced by different class orderings
Yükleniyor...
Dosyalar
Tarih
2016
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this paper, we discuss a novel approach to incrementally construct a rule ensemble. The approach constructs an ensemble from a dynamically generated set of rule classifiers. Each classifier in this set is trained by using a different class ordering. We investigate criteria including accuracy, ensemble size, and the role of starting point in the search. Fusion is done by averaging. Using 22 data sets, floating search finds small, accurate ensembles in polynomial time.
Açıklama
Anahtar Kelimeler
Ensemble construction, Rule sets, Eigenclassifiers, Combination, Diversity, Selection, Training, Optimization, Feature extraction, Search problems, Pattern recognition, Computers, Technological innovation, Pattern classification, Set theory, Incremental construction, Dynamically generated set, Rule classifiers, Polynomial time
Kaynak
2016 23rd International Conference on Pattern Recognition (ICPR)
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
Cilt
Sayı
Künye
Yıldız, O. T. & Ulaş, A. (2016). Incremental construction of rule ensembles using classifiers produced by different class orderings. Paper presented at the 2016 23rd International Conference on Pattern Recognition (ICPR), 492-497. doi:10.1109/ICPR.2016.7899682
