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  • [外文期刊] Jingkuan Li Hong Zhao William Zhu 《International journal of machine learning and cybernetics》, 2015 3
    Feature selection is an important problem in data mining and machine learning. Cost-sensitive feature selection over the past 10 years has seen increasingly rapid advances. Recently, a fast randomized ...
    Feature selectionRestart strategyTest costTime constraint
  • [会议论文] ,2014 - The 9th International Conference on Rough Sets and Knowledge Technology (RSKT 2014)(第九届粗糙集与知识技术国际会议)
      The minimal test cost attribute reduction is an important component in data mining applications,and plays a key role in cost-sensitive learning.Recently,several algorithms are proposed to address thi...
    Cost-sensitive learningMinimal test costAttribute reductionGranular computingBiologically-inspired algorithm
  • [会议论文] ,2014 - The 9th International Conference on Rough Sets and Knowledge Technology (RSKT 2014)(第九届粗糙集与知识技术国际会议)
      Minimal test cost attribute reduction is an important problem in cost-sensitive learning since it reduces the dimensionality of the attributes space.To address this issue,many heuristic algorithms ha...
    Cost-sensitive learningGranular computingAttribute reductionTest costLogarithmic weighted algorithm
  • [会议论文] ,2014 - The 9th International Conference on Rough Sets and Knowledge Technology (RSKT 2014)(第九届粗糙集与知识技术国际会议)
      Recommender systems are popular in e-commerce as they provide users with items of interest.Existing top-K approaches mine the K strongest granular association rules for each user,and then recommend r...
    Granular computingrecommender systemgranule association rulesconfidencesignificance
  • [会议论文] ,2014 - The 9th International Conference on Rough Sets and Knowledge Technology (RSKT 2014)(第九届粗糙集与知识技术国际会议)
      As a technique for granular computing,rough sets deal with the vagueness and granularity in information systems.Covering-based rough sets are natural extensions of the classical rough sets by relaxin...
    Granular computingcoveringrough setneighborhoodinclusion degreenetwork security
  • [会议论文] ,2014 - The 9th International Conference on Rough Sets and Knowledge Technology (RSKT 2014)(第九届粗糙集与知识技术国际会议)
      As one of three basic theories of granular computing,rough set theory provides a useful tool for dealing with the granularity in information systems.Covering-based rough set theory is a generalizatio...
    CoveringRough setGranular computingApproximation operatorSet-valued information system
  • [会议论文] ,2014 - The 2014 10th International Conference on Natural Computation (ICNC 2014) and the 2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2014)(第十届自然计算和第十一届模糊系统与知识发现国际会议)
      Rough set theory has been proposed by Pawlak as a useful and powerful tool for dealing with uncertainty,granularity,and incompleteness of knowledge in information systems.Matroid theory is a branch o...
    rough setcoveringapproximation operatormatroidcircuitcovering-circuit matroid
  • [外文期刊] Jingqian Wang William Zhu Fei-Yue Wang Guilong Liu 《International journal of machine learning and cybernetics》, 2014 6
    Coverings are a useful form of data structure, and covering-based rough sets provide an effective tool to cope with this type of data. However, many important problems such as covering reduction in cov...
    CoveringRough setNeighborhood MatroidEulerian matroid
  • [外文期刊] Hua Yao William Zhu Fei-Yue Wang 《International journal of machine learning and cybernetics》, 2014 6
    By the augmentation axiom of matroids, given two independent sets whose cardinalities are not equal, there exists some other independent set of which the independent set with smaller cardinality is a p...
    Granular computingSecondary basis unique augmentation matroidRank-preserving weak-mapUnion minimal matroidBasis unique exchange matroid
  • [外文期刊] Fan Min Qinghua Hu William Zhu 《International journal of approximate reasoning》, ISTIC EI SCI PKU CSSCI 2014 1 Pt.2
    Feature selection is an important preprocessing step in machine learning and data mining. In real-world applications, costs, including money, time and other resources, are required to acquire the featu...
    Feature selectionCost-sensitive learningConstraint satisfaction problemBacktracking algorithmHeuristic algorithmDecision-theoretic rough sets
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