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A set-cover-based approach for the test-cost-sensitive attribute reduction problem

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Abstract

In data mining application, the test-cost-sensitive attribute reduction is an important task which aims to decrease the test cost of data. In operational research, the set cover problem is a typical optimization problem and has a long investigation history compared to the attribute reduction problem. In this paper, we employ the methods of set cover problem to deal with the test-cost-sensitive attribute reduction. First, we equivalently transform the test-cost-sensitive reduction problem into the set cover problem by using a constructive approach. It is shown that computing a reduct of a decision system with minimal test cost is equal to computing an optimal solution of the set cover problem. Then, a set-cover-based heuristic algorithm is introduced to solve the test-cost-sensitive reduction problem. In the end, we conduct several numerical experiments on data sets from UCI machine learning repository. Experimental results indicate that the set-cover-based algorithm has superior performances in most cases, and the algorithm is efficient on data sets with many attributes.

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Acknowledgments

This work is supported by Grants from National Natural Science Foundation of China (Nos. 61573321, 61272021, 61202206 and 61173181), Zhejiang Provincial Natural Science Foundation of China (Nos. LZ12F03002, LY14F030001), Open Foundation from Marine Sciences in the Most Important Subjects of Zhejiang (No. 20130109), and Scientific Research Start-up Fund of Zhejiang Ocean University (No. 21065014715).

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Authors and Affiliations

  1. School of Mathematics, Physics and Information Science, Zhejiang Ocean University, Zhoushan, 316022, Zhejiang, China

    Anhui Tan, Weizhi Wu & Yuzhi Tao

  2. Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province, Zhoushan, 316022, Zhejiang, China

    Anhui Tan

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  1. Anhui Tan
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  2. Weizhi Wu
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  3. Yuzhi Tao
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Correspondence to Anhui Tan.

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Author Anhui Tan declares that he has no conflict of interest. Author Weizhi Wu declares that he has no conflict of interest. Author Yuzhi Tao declares that she has no conflict of interest.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by V. Loia.

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Tan, A., Wu, W. & Tao, Y. A set-cover-based approach for the test-cost-sensitive attribute reduction problem. Soft Comput 21, 6159–6173 (2017). https://doi.org/10.1007/s00500-016-2173-3

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