VC-dimension of rule sets
Yükleniyor...
Dosyalar
Tarih
2014-12-04
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE Computer Soc
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this paper, we give and prove lower bounds of the VC-dimension of the rule set hypothesis class where the input features are binary or continuous. The VC-dimension of the rule set depends on the VC-dimension values of its rules and the number of inputs.
Açıklama
Anahtar Kelimeler
VC-Dimension, Rule Sets, Computers, Decision trees, Labeling, Pattern recognition, Statistical learning, Training, Vectors, Learning (artificial intelligence), Set theory, VC-dimension values, Binary input features, Continuous input features, Lower bounds, Rule set hypothesis class
Kaynak
International Conference on Pattern Recognition
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
Cilt
Sayı
Künye
Yıldız, O. T. (2014). VC-dimension of rule sets. Paper presented at the International Conference on Pattern Recognition, 3576-3581. doi:10.1109/ICPR.2014.615
