NDLI: Forest pruning based on Tree-Node Order

Content Provider	IEEE Xplore Digital Library
Author	Huaping Guo Ming Fan Yangdong Ye
Copyright Year	2011
Description	Author affiliation: School of Information Engineering, ZhengZhou University, China (Huaping Guo; Ming Fan; Yangdong Ye)
Abstract	This paper proposes a forest pruning method called F-Pruning to improve the performance of ensembles based on decision trees. Instead of trimming each decision tree separately or/and selecting an optimal or sub-optimal subset of base classifiers to form an ensemble, F-Pruning takes a fixed number of trimmed or untrimmed decision trees as a forest (ensemble) and prunes branches directly from the forest to improve the ensemble accuracy. F-Pruning is a greedy algorithm, which uses the impurity measure and the number of examples in each node to determine the rank of the node, and prunes the node with lowest rank each time. In this way, F-Pruning achieves a fast forest pruning and reduces the size of final ensembles significantly. Our experiments show that, in comparison with ensembles built by combining trimmed or untrimmed decision trees, forests pruned by F-Pruning have better generalization capability in most of data sets. Additionally, our experiments show that executing F-Pruning on sub-forests selected by EPIC [1] can also reduce the size of the final ensembles significantly and improve their classification accuracies slightly.
Starting Page	71
Ending Page	76
File Size	178692
Page Count	6
File Format	PDF
ISBN	9781424487271
e-ISBN	9781424487288
DOI	10.1109/CSAE.2011.5952636
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Radio frequency Training Tree-Node Order Accuracy Impurities Forest Pruning Ensemble Selection Vegetation Complexity theory Decision trees
Content Type	Text
Resource Type	Article

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