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Volumn 5009 LNAI, Issue , 2008, Pages 276-283

The incremental learning methodology of VPRS based on complete information system

Author keywords

Accuracy; Coverage; Incremental learning; VPRS

Indexed keywords

DATA STRUCTURES; DECISION MAKING; INFORMATION SYSTEMS; PROBLEM SOLVING; ROUGH SET THEORY;

EID: 44649121597     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-79721-0_40     Document Type: Conference Paper
Times cited : (6)

References (14)
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    • Beynon, M.: Reducts within the variable precision rough sets model: a further investigation. European Journal of Operational Research 134, 592-605 (2001)
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    • Beynon, M.1
  • 4
    • 1642525195 scopus 로고    scopus 로고
    • Approaches to knowledge reduction based on variable precision rough sets model
    • Mi, J.S.: Approaches to knowledge reduction based on variable precision rough sets model. Information Sciences 159, 255-272 (2004)
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    • Mi, J.S.1
  • 5
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    • Knowledge Reducts Based on Variable Precision Rough Set Theory
    • Mi, J.S.: Knowledge Reducts Based on Variable Precision Rough Set Theory. Systems Engineering-theory and Practice 24, 116-120 (2004)
    • (2004) Systems Engineering-theory and Practice , vol.24 , pp. 116-120
    • Mi, J.S.1
  • 6
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    • Incremental learning based on Variable Precision Rough set Model
    • Li., L.: Incremental learning based on Variable Precision Rough set Model. Computer Science 26, 55-61 (1999)
    • (1999) Computer Science , vol.26 , pp. 55-61
    • Li, L.1
  • 7
    • 4444321041 scopus 로고    scopus 로고
    • Rough Set Approach to incremental acquisition of rules
    • An, L.P.: Rough Set Approach to incremental acquisition of rules. Journal of Nankai University 36, 98-103 (2003)
    • (2003) Journal of Nankai University , vol.36 , pp. 98-103
    • An, L.P.1
  • 8
    • 33748597941 scopus 로고    scopus 로고
    • R Mining fuzzy β-certain and β-possible rules from quantitative data based on the variable precision rough-set model
    • Hong, T.P.: R Mining fuzzy β-certain and β-possible rules from quantitative data based on the variable precision rough-set model. Expert Systems with Applications 32, 223-232 (2007)
    • (2007) Expert Systems with Applications , vol.32 , pp. 223-232
    • Hong, T.P.1
  • 9
    • 44649191063 scopus 로고    scopus 로고
    • Variable precision rough set theory and data discretisation: An application to corporate failure prediction
    • Beynon, M.: Variable precision rough set theory and data discretisation: an application to corporate failure prediction. The International Journal of Management Science 29, 576-581 (2001)
    • (2001) The International Journal of Management Science , vol.29 , pp. 576-581
    • Beynon, M.1
  • 10
    • 27744529900 scopus 로고    scopus 로고
    • Precision parameter in the variable precision rough sets model: An application
    • Su, C.T.: Precision parameter in the variable precision rough sets model: an application. The International Journal of Management Science 34, 149-157 (2006)
    • (2006) The International Journal of Management Science , vol.34 , pp. 149-157
    • Su, C.T.1
  • 13
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    • Self-determining variable precision value approach based on variable precision rough sets model
    • Cheng, Y.S., Zhang, Y.S.: Self-determining variable precision value approach based on variable precision rough sets model. Journal of System Simulation 19, 2555-2558 (2007)
    • (2007) Journal of System Simulation , vol.19 , pp. 2555-2558
    • Cheng, Y.S.1    Zhang, Y.S.2
  • 14
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    • Yao, Y.Y.: Decision-Theoretic Rough Set Models. In: Yao, J., Lingras, P., Wu, W.-Z., Szczuka, M., Cercone, N.J., Ślȩzak, D. (eds.) RSKT 2007. LNCS (LNAI), 4481, pp. 1-12. Springer, Heidelberg (2007)
    • Yao, Y.Y.: Decision-Theoretic Rough Set Models. In: Yao, J., Lingras, P., Wu, W.-Z., Szczuka, M., Cercone, N.J., Ślȩzak, D. (eds.) RSKT 2007. LNCS (LNAI), vol. 4481, pp. 1-12. Springer, Heidelberg (2007)


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.