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  1. No Access

    Article

    An improved decision tree algorithm based on boundary mixed attribute dependency

    As an effective extension of rough set theory, the variable precision neighborhood rough set model has been applied to the attribute dependency-based improvement of decision tree algorithm of the solution conc...

    Bowen Lin, Caihui Liu, Duoqian Miao in Applied Intelligence (2024)

  2. No Access

    Article

    An improved ID3 algorithm based on variable precision neighborhood rough sets

    The classical ID3 decision tree algorithm cannot directly handle continuous data and has a poor classification effect. Moreover, most of the existing approaches use a single mechanism for node measurement, whi...

    Caihui Liu, Jianying Lai, Bowen Lin, Duoqian Miao in Applied Intelligence (2023)

  3. No Access

    Chapter and Conference Paper

    Hierarchical Multi-granulation Sequential Three-Way Decisions

    In granular computing, a single conditional attribute is usually used as a view to describe the target concept, and each view can choose a specific level of granularity to describe the object in the hierarchic...

    Chengxin Hong, ** Qian, Haoying Jiang, Zhigang Tong, Ying Yu, Caihui Liu in Rough Sets (2022)

  4. No Access

    Chapter and Conference Paper

    Covering-Based Optimistic-Pessimistic Multigranulation Decision-Theoretic Rough Sets

    Multigranulation decision-theoretic rough sets (MDTRS) is a workable model for real-world decision making. The fruitful research achievements of the use of these models have been reported in different aspects....

    Caihui Liu, ** Qian, Nan Zhang, Meizhi Wang in Rough Sets (2018)

  5. No Access

    Chapter and Conference Paper

    Covering-Based Optimistic Multigranulation Decision-Theoretic Rough Sets Based on Maximal Descriptors

    This paper investigates decision-theoretic rough set approach in the frameworks of multi-covering approximation space. We mainly discuss optimistic multigranulation decision-theoretic rough sets by employing m...

    Caihui Liu, Meizhi Wang, Nan Zhang in Rough Sets (2017)

  6. No Access

    Chapter and Conference Paper

    Attribute Reduction in Utility-Based Decision-Theoretic Rough Set Models

    Decision-theoretic rough set (DTRS) model, proposed by Yao in the early 1990’s, introduces Bayesian decision procedure and loss function in rough set theory. Considering utility function in decision processing...

    Nan Zhang, Lili Jiang, Caihui Liu in Rough Sets (2017)

  7. No Access

    Chapter and Conference Paper

    Optimistic Decision-Theoretic Rough Sets in Multi-covering Space

    This paper discusses optimistic multigranulation decision-theoretic rough sets in multi-covering space. First, by using the strategy “seeking commonality while preserving difference”, we propose the notion of ...

    Caihui Liu, Meizhi Wang in Rough Sets (2016)

  8. No Access

    Chapter and Conference Paper

    A New Subsystem-Based Definition of Generalized Rough Set Model

    The generalization of Pawlak rough set model always attracts the attentions of the researchers in the rough set society. In this paper, we propose a new subsystem-based definition of generalized rough set mode...

    Caihui Liu, Meizhi Wang, Yanfei Dai… in Rough Sets, Fuzzy Sets, Data Mining, and G… (2015)

  9. No Access

    Article

    Graph embedding discriminant analysis for face recognition

    This paper develops a supervised discriminant technique, called graph embedding discriminant analysis (GEDA), for dimensionality reduction of high-dimensional data in small sample size problems. GEDA can be se...

    Cairong Zhao, Zhihui Lai, Duoqian Miao, Zhihua Wei… in Neural Computing and Applications (2014)

  10. No Access

    Chapter and Conference Paper

    Multi-granulation Rough Sets Based on Central Sets

    Exploring rough sets from the viewpoint of multi-granulation has become one of the promising topics in rough set theory, in which lower or upper approximations are approximated by multiple binary relations. Th...

    Caihui Liu, Meizhi Wang, Yujiang Liu, Min Wang in Rough Sets and Knowledge Technology (2014)

  11. No Access

    Chapter and Conference Paper

    Covering Rough Set Model Based on Multi-granulations

    The paper extends the covering rough set model based on single granulation to the covering rough set model based on multi- granulations, which is named CMGRS. The lower and upper approximations of a set in a c...

    Caihui Liu, Duoqian Miao in Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (2011)