Soft decision trees
Yükleniyor...
Dosyalar
Tarih
2012
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
We discuss a novel decision tree architecture with soft decisions at the internal nodes where we choose both children with probabilities given by a sigmoid gating function. Our algorithm is incremental where new nodes are added when needed and parameters are learned using gradient-descent. We visualize the soft tree fit on a toy data set and then compare it with the canonical, hard decision tree over ten regression and classification data sets. Our proposed model has significantly higher accuracy using fewer nodes.
Açıklama
Anahtar Kelimeler
Regression tree analysis, Accuracy, Training, Pattern recognition, Educational institutions, Interpolation, Data visualisation, Decision trees, Gradient methods, Pattern classification, Probability, Regression analysis, Soft decision tree architecture, Internal nodes, Probabilities, Sigmoid gating function, Incremental algorithm, Gradient-descent algorithm, Toy data set, Regression data sets, Classification data sets, Classification (of information), Data mining, Gating functions, Gradient-descent, Hard decisions, Soft decision, Toy data, Tree architectures
Kaynak
International Conference on Pattern Recognition
WoS Q Değeri
N/A
Scopus Q Değeri
2-s2.0-84874569105
N/A
N/A
Cilt
Sayı
Künye
İrsoy, O., Yıldız, O. T. & Alpaydın, A. İ. E. (2012). Soft decision trees. Paper presented at the International Conference on Pattern Recognition, 1819-1822.
