[1] |
Thangavel K, Pethalakshmi A. Dimensionality reduction based on rough set theory:A review[J]. Applied Soft Computing,2009,9(1):112.
|
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Table 2Classification accuracy analysis of the attributes reduction of NS表2邻域决策系统属性约简分类精度对比数据集
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(初始分类精度)实验内容本文方法方法1方法2方法3属性个数14151715Waveform
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(80.8±7.4)耗时/s79.690.3107.2104.6分类精度82.2±5.178.4±4.880.6±5.679.4±5.3属性个数10131312Vehicle
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(76.6±5.9)耗时/s11.213.914.714.0分类精度78.6±4.373.5±5.375.7±4.576.5±4.2属性个数10121110Wdbc
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(96.4±5.0)耗时/s11.318.015.615.8分类精度97.2±3.296.5±5.994.2±4.896.8±5.2属性个数5666Ecoli
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(83.6±7.3)耗时/s4.95.45.86.7分类精度85.0±4.979.8±6.783.4±4.484.0±5.1属性个数1281514Image Seg
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(65.1±5.7)耗时/s18.515.425.323.7分类精度67.3±3.059.2±4.066.3±4.266.8±5.3[2]Miao Duoqian, Li Daoguo. Rough set theory, algorithms and applications [M].Beijing:Tsinghua University Press,2008:2434.(in Chinese)
|
[3] |
Wang C,Wu C,Chen D. A systematic study on attribute reduction with rough sets based on general binary relations[J]. Information Sciences,2008,178(9):22372261.
|
[4] |
Deng T,Yang C,Wang X. A reduct derived from feature selection[J]. Pattern Recognition Letters,2012,33(12):16381646.
|
[5] |
Magro M C,Pinceti P. A confirmation technique for predictive maintenance using the rough set theory[J]. Computers & Industrial Engineering,2009,56(4):13191327.
|
[6] |
Jiang F,Sui Y. A novel approach for discretization of continuous attributes in rough set theory[J]. KnowledgeBased Systems,2015,73:324334.
|
[7] |
Hu Q,Yu D,Liu J. Neighborhood rough set based heterogeneous feature subset selection[J]. Information Sciences,2008,178(18):35773594.
|
[8] |
Chen Y,Wu K. An entropybased uncertainty measurement approach in neighborhood systems[J]. Information Sciences,2014,279:239250.
|
[9] |
Hu Qinghua,Zhao Hui, Yu Daren. Efficient symbolic and numerical attribute reduction with neighborhood rough sets[J]. Pattern Recognition and Artificial Intelligence,2008,21(12):732738.(in Chinese)
|
[10] |
Zhu W,Si G. Neighborhood effective information ratio for hybrid feature subset evaluation and selection[J]. Neurocomputing,2013,99:2537.
|
[11] |
Hu Q,Che X. Feature evaluation and selection based on neighborhood soft margin[J]. Neurocomputing,2010,73(10):21142124.
|
[12] |
Zhu Wenzhi,Si Gangquan, Zhang Yanbin,et al. Feature selection algorithm based on neighborhood decision distinguishing rate[J]. Journal of Xi’an Jiaotong University,2013,47(2):2027.(in Chinese)
|
[13] |
Wang Xing. Big data analysis:Methods and applications[M].Beijing:Tsinghua University Press,2013:8391.(in Chinese)
|
|
附中文参考文献:
|
[2] |
苗夺谦,李道国.粗糙集理论、算法与应用[M].北京:清华大学出版社,2008:2434.
|
[9] |
胡清华,赵辉,于达仁.基于邻域粗糙集的符号与数值属性快速约简算法[J].模式识别与人工智能,2008,21(12):732738.
|
[12] |
诸文智,司刚全,张彦斌.采用邻域决策分辨率的特征选择算法[J].西安交通大学学报,2013,47(2):2027.
|
[13] |
王星.大数据分析:方法与应用[M].北京,清华大学出版社,2013:8391.
|