Cost-complexity Pruning
Cost-Complexity Pruning is a model simplification technique in decision tree learning that belongs to the class of post-pruning methods, distinguished by its use of a complexity parameter to balance the trade-off between tree size and classification accuracy through nested subtree selection.
13
Publications
387
Citations
37
Authors
20
Institutions
Publications per year
2017–2026
4
Parents
13
Pruning Decision Tree Using Genetic Algorithms
Jie Chen, Xizhao Wang, Junhai Zhai · 2009 · 37 citations
A Dynamic Programming Based Pruning Method for Decision Trees
Xiao‐Bai Li, James R. Sweigart, James T. C. Teng et al. · INFORMS journal on computing · 2001 · 37 citations
1–5 of 13
37
1
h-index
1
h-index
1
h-index
1
h-index
1
h-index
1–5 of 37
20
University of Kashmir
Srinagar, India
1 h-index
3 publications
75 citations

University of Toronto
Toronto, Canada
1 h-index
1 publications
22 citations

Hebei University
Baoding, China
1 h-index
3 publications
111 citations

Johns Hopkins University
Baltimore, United States
1 h-index
1 publications
59 citations
Columbia University
New York, United States
1 h-index
2 publications
144 citations
Vytautas Magnus University
Kaunas, Lithuania
1 h-index
2 publications
30 citations
University of South Carolina
Columbia, United States
1 h-index
4 publications
148 citations
Fred Hutch Cancer Center
Seattle, United States
1 h-index
1 publications
22 citations
1–8 of 20
2 publications · 58 citations
2
h-index
1 publications · 33 citations
1
h-index
RCER · 1 publications · 25 citations
1
h-index
1 publications · 72 citations
1
h-index
JCGS · 1 publications · 22 citations
1
h-index
1–5