[1]ZHAO Tianna,MIAO Duoqian,MI Jusheng,et al.Multi-adjoint three-way decisions on heterogeneous data[J].CAAI Transactions on Intelligent Systems,2019,14(6):1092-1099.[doi:10.11992/tis.201905048]
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Multi-adjoint three-way decisions on heterogeneous data
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
14
Number of periods:
2019 6
Page number:
1092-1099
Column:
学术论文—机器感知与模式识别
Public date:
2019-11-05
- Title:
- Multi-adjoint three-way decisions on heterogeneous data
- Keywords:
- heterogeneous data; fuzzy rough set; three-way decisions; multi-adjoint; cost-sensitive; knowledge representation; classification
- CLC:
- TP391
- DOI:
- 10.11992/tis.201905048
- Abstract:
- Considering the problem of knowledge representation and classification relating to heterogeneous data, a cost-sensitive multi-adjoint fuzzy rough set model is proposed for the effective representation of heterogeneous data and in order to solve the classification problem of heterogeneous data, the idea of three-way decisions is introduced. Moreover, two improvements are made on the basis of the multi-adjoint model: 1) A revised probability definition is presented to approximately characterize the cost-sensitive fuzzy rough set model. 2) Based on the idea of the dual quantization delay cost objective function, a novel three-way decisions model is constructed for heterogeneous data. This model has the following characteristics: 1) Multiple adjoint pairs are introduced to simulate the relationship of heterogeneous complementarity between numerical attribute and categorical attribute. 2) The multi-adjoint operator is defined to fully express the preference among different attributes. 3) A fuzzy rough set is combined to overcome the uncertainty of the classification problem. 4) The cost of acquiring both numerical and categorical attributes is considered to improve the possibility of application to real life. The effectiveness of the model is verified in the heterogeneous dataset.
- References:
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Last Update:
2019-12-25