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Combining multiple class distribution modified subsamples in a single tree
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DOI：10.1016/j.patrec.2006.08.013.png)
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摘要
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This work describes the Consolidated Tree Construction (CTC) algorithm: a single tree is built based on a set of subsamples. This way the explaining capacity of the classifier is not lost even if many subsamples are used. We show how CTC algorithm can use undersampling to change class distribution without loss of information, building more accurate classifiers than C4.5. (c) 2006 Elsevier B.V. All rights reserved.
Keyword:
class distribution
decision tree
sampling
comprehensibility
C4.5
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3.3
论文数:
8.0K
被引数:
1.6W
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