The Cascade Decision-Tree Improvement Algorithm Based on Unbalanced Data Set

Authors:
Wang Yi
Affiliations:
-
Venue:
CMC '10 Proceedings of the 2010 International Conference on Communications and Mobile Computing - Volume 01
Year:
2010

Citing 0
Cited 1

An improved CART decision tree for datasets with irrelevant feature

SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part I

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Abstract

In the past research, the data mining that using single classifier can not obtain satisfactory results. This paper proposed an improved decision-tree classification algorithm MAdaBoost for solving the customers’ chruning problem. The idea of this algorithm is that using cascaded structure to construct more decision tree classifier based on AdaBoost. This tree have a better classification results according to the experimental results.