Taiga: Performance Optimization of the C4.5 Decision Tree Construction Algorithm |
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Authors: | Yi Yang;Wenguang Chen; |
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Institution: | Yi Yang;Wenguang Chen;Department of Computer Science and Technology,Tsinghua University;Technology Innovation Center at Yinzhou,Yangtze Delta Region Institute of Tsinghua University; |
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Abstract: | Classification is an important machine learning problem, and decision tree construction algorithms are an important class of solutions to this problem. Rain Forest is a scalable way to implement decision tree construction algorithms. It consists of several algorithms, of which the best one is a hybrid between a traditional recursive implementation and an iterative implementation which uses more memory but involves less write operations. We propose an optimized algorithm inspired by Rain Forest. By using a more sophisticated switching criterion between the two algorithms, we are able to get a performance gain even when all statistical information fits in memory. Evaluations show that our method can achieve a performance boost of 2.8 times in average than the traditional recursive implementation. |
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