메뉴 건너뛰기




Volumn 148, Issue 1-2, 2003, Pages 335-383

Possibilistic instance-based learning

Author keywords

Fuzzy set theory; Instance based learning; Machine learning; Nearest neighbor classification; Possibility theory; Probability

Indexed keywords

FUZZY SETS; LEARNING SYSTEMS; PROBABILITY;

EID: 0042129877     PISSN: 00043702     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0004-3702(03)00019-5     Document Type: Article
Times cited : (35)

References (86)
  • 1
    • 85152621496 scopus 로고
    • Incremental, instance-based learning of independent and graded concept descriptions
    • Ithaca, NY, San Mateo, CA: Morgan Kaufmann
    • Aha D.W. Incremental, instance-based learning of independent and graded concept descriptions. Proc. 6th Internat. Workshop on Machine Learning, Ithaca, NY. 1989;387-391 Morgan Kaufmann, San Mateo, CA.
    • (1989) Proc. 6th Internat. Workshop on Machine Learning , pp. 387-391
    • Aha, D.W.1
  • 2
    • 0000217085 scopus 로고
    • Tolerating noisy, irrelevant and novel attributes in instance-based learning algorithms
    • Aha D.W. Tolerating noisy, irrelevant and novel attributes in instance-based learning algorithms. Internat. J. Man-Machine Stud. 36:1992;267-287.
    • (1992) Internat. J. Man-Machine Stud. , vol.36 , pp. 267-287
    • Aha, D.W.1
  • 3
    • 0004267735 scopus 로고    scopus 로고
    • Dordrecht: Kluwer Academic
    • Aha D.W. Lazy Learning. 1997;Kluwer Academic, Dordrecht.
    • (1997) Lazy Learning
    • Aha, D.W.1
  • 4
  • 5
    • 0017957910 scopus 로고
    • A note on distance-weighted k-nearest neighbor rules
    • Bailey T., Jain A.K. A note on distance-weighted k-nearest neighbor rules. IEEE Trans. Systems Man Cybernet. 8:(4):1978;311-313.
    • (1978) IEEE Trans. Systems Man Cybernet. , vol.8 , Issue.4 , pp. 311-313
    • Bailey, T.1    Jain, A.K.2
  • 6
    • 0002794598 scopus 로고
    • A fuzzy extended k-nearest neighbors rule
    • Béreau M., Dubuisson B. A fuzzy extended k-nearest neighbors rule. Fuzzy Sets and Systems. 44:1991;17-32.
    • (1991) Fuzzy Sets and Systems , vol.44 , pp. 17-32
    • Béreau, M.1    Dubuisson, B.2
  • 10
    • 85118837783 scopus 로고
    • Addressing the selective superiority problem: Automatic algorithm for model class selection
    • Brodley C.E. Addressing the selective superiority problem: Automatic algorithm for model class selection. Proc. 10th Machine Learning Conference. 1993;17-24.
    • (1993) Proc. 10th Machine Learning Conference , pp. 17-24
    • Brodley, C.E.1
  • 11
    • 0016127071 scopus 로고
    • Finding prototypes for nearest neighbor classifiers
    • Chang C.L. Finding prototypes for nearest neighbor classifiers. IEEE Trans. Comput. 23:(11):1974;1179-1184.
    • (1974) IEEE Trans. Comput. , vol.23 , Issue.11 , pp. 1179-1184
    • Chang, C.L.1
  • 12
    • 0014710323 scopus 로고
    • On optimum recognition error and reject tradeoff
    • Chow C.K. On optimum recognition error and reject tradeoff. IEEE Trans. Inform. Theory. 16:1970;41-46.
    • (1970) IEEE Trans. Inform. Theory , vol.16 , pp. 41-46
    • Chow, C.K.1
  • 15
    • 0018923633 scopus 로고
    • Nosing around the neighborhood: A new system structure and classification rule for recognition in partially exposed environments
    • Dasarathy B.V. Nosing around the neighborhood: A new system structure and classification rule for recognition in partially exposed environments. IEEE Trans. Pattern Analysis and Machine Intelligence. 2:(1):1980;67-71.
    • (1980) IEEE Trans. Pattern Analysis and Machine Intelligence , vol.2 , Issue.1 , pp. 67-71
    • Dasarathy, B.V.1
  • 17
    • 0024255125 scopus 로고
    • Training sets and a priori probabilities with the nearest neighbor method of pattern classification
    • Davies E.R. Training sets and a priori probabilities with the nearest neighbor method of pattern classification. Pattern Recognition Lett. 8:(1):1988;11-13.
    • (1988) Pattern Recognition Lett. , vol.8 , Issue.1 , pp. 11-13
    • Davies, E.R.1
  • 18
    • 0032026327 scopus 로고    scopus 로고
    • Machine learning from examples: Inductive and lazy methods
    • Lopez de Mantaras R., Armengol E. Machine learning from examples: Inductive and lazy methods. Data Knowledge Engrg. 25:1998;99-123.
    • (1998) Data Knowledge Engrg. , vol.25 , pp. 99-123
    • Lopez de Mantaras, R.1    Armengol, E.2
  • 19
    • 0029307876 scopus 로고
    • A k-nearest neighbor classification rule based on Dempster-Shafer Theory
    • Denoeux T. A k-nearest neighbor classification rule based on Dempster-Shafer Theory. IEEE Trans. Systems Man Cybernet. 25:(5):1995;804-813.
    • (1995) IEEE Trans. Systems Man Cybernet. , vol.25 , Issue.5 , pp. 804-813
    • Denoeux, T.1
  • 20
    • 0018656141 scopus 로고
    • Pattern recognition with partly missing data
    • Dixon J.K. Pattern recognition with partly missing data. IEEE Trans. Systems Man Cybernet. 9:(10):1979;617-621.
    • (1979) IEEE Trans. Systems Man Cybernet. , vol.9 , Issue.10 , pp. 617-621
    • Dixon, J.K.1
  • 21
    • 85168157659 scopus 로고
    • Rule induction and instance-based learning: A unified approach
    • C.S. Mellish. Montreal, Quebec, San Mateo, CA: Morgan Kaufmann
    • Domingos P. Rule induction and instance-based learning: A unified approach. Mellish C.S. Proc. IJCAI-95, Montreal, Quebec. 1995;1226-1232 Morgan Kaufmann, San Mateo, CA.
    • (1995) Proc. IJCAI-95 , pp. 1226-1232
    • Domingos, P.1
  • 22
    • 0030216565 scopus 로고    scopus 로고
    • Unifying instance-based and rule-based induction
    • Domingos P. Unifying instance-based and rule-based induction. Machine Learning. 24:1996;141-168.
    • (1996) Machine Learning , vol.24 , pp. 141-168
    • Domingos, P.1
  • 25
    • 84948155046 scopus 로고    scopus 로고
    • Flexible control of case-based prediction in the framework of possibility theory
    • E. Blanzieri, & L. Portinale. Advances in Case-Based Reasoning, 5th European Workshop on Case-Based Reasoning, Trento, Italym, Berlin: Springer
    • Dubois D., Hüllermeier E., Prade H. Flexible control of case-based prediction in the framework of possibility theory. Blanzieri E., Portinale L. Advances in Case-Based Reasoning, Proc. EWCBR-2000, 5th European Workshop on Case-Based Reasoning, Trento, Italy. 2000;61-73 Springer, Berlin.
    • (2000) Proc. EWCBR-2000 , pp. 61-73
    • Dubois, D.1    Hüllermeier, E.2    Prade, H.3
  • 26
    • 0002076565 scopus 로고    scopus 로고
    • Formalizing case-based inference using fuzzy rules
    • S.K. Pal, D.Y. So, & T. Dillon. Berlin: Springer
    • Dubois D., Hüllermeier E., Prade H. Formalizing case-based inference using fuzzy rules. Pal S.K., So D.Y., Dillon T. Soft Computing in Case-Based Reasoning. 2000;47-72 Springer, Berlin.
    • (2000) Soft Computing in Case-Based Reasoning , pp. 47-72
    • Dubois, D.1    Hüllermeier, E.2    Prade, H.3
  • 27
    • 0036601875 scopus 로고    scopus 로고
    • Fuzzy set-based methods in instance-based reasoning
    • Dubois D., Hüllermeier E., Prade H. Fuzzy set-based methods in instance-based reasoning. IEEE Trans. Fuzzy Systems. 10:(3):2002;322-332.
    • (2002) IEEE Trans. Fuzzy Systems , vol.10 , Issue.3 , pp. 322-332
    • Dubois, D.1    Hüllermeier, E.2    Prade, H.3
  • 28
  • 31
    • 0010965368 scopus 로고
    • When upper probabilities are possibility measures
    • Dubois D., Prade H. When upper probabilities are possibility measures. Fuzzy Sets and Systems. 49:1992;65-74.
    • (1992) Fuzzy Sets and Systems , vol.49 , pp. 65-74
    • Dubois, D.1    Prade, H.2
  • 32
    • 0030577310 scopus 로고    scopus 로고
    • What are fuzzy rules and how to use them
    • Dubois D., Prade H. What are fuzzy rules and how to use them. Fuzzy Sets and Systems. 84:1996;169-185.
    • (1996) Fuzzy Sets and Systems , vol.84 , pp. 169-185
    • Dubois, D.1    Prade, H.2
  • 33
    • 0002571253 scopus 로고    scopus 로고
    • Possibility theory: Qualitative and quantitative aspects
    • D.M. Gabbay, & P. Smets. Dordrecht: Kluwer Academic
    • Dubois D., Prade H. Possibility theory: Qualitative and quantitative aspects. Gabbay D.M., Smets P. Handbook of Defeasible Reasoning and Uncertainty Management Systems, Vol. 1. 1998;169-226 Kluwer Academic, Dordrecht.
    • (1998) Handbook of Defeasible Reasoning and Uncertainty Management Systems , vol.1 , pp. 169-226
    • Dubois, D.1    Prade, H.2
  • 34
    • 84937396875 scopus 로고    scopus 로고
    • Not impossible vs. guaranteed possible in fusion and revision
    • Proc. ESCQARU-2001, Toulouse, France Berlin: Springer
    • Dubois D., Prade H., Smets P. Not impossible vs. guaranteed possible in fusion and revision. Proc. ESCQARU-2001, Toulouse, France. Lecture Notes in Comput. Sci. 2143:2001;522-531 Springer, Berlin.
    • (2001) Lecture Notes in Comput. Sci , vol.2143 , pp. 522-531
    • Dubois, D.1    Prade, H.2    Smets, P.3
  • 35
    • 84945246241 scopus 로고    scopus 로고
    • A new perspective on reasoning with fuzzy rules
    • N.R. Pal, & M. Sugeno. Advances in Soft Computing, Proc. AFSS International Conference on Fuzzy Systems, Calcutta, India, Berlin: Springer
    • Dubois D., Prade H., Ughetto L. A new perspective on reasoning with fuzzy rules. Pal N.R., Sugeno M. Advances in Soft Computing, Proc. AFSS International Conference on Fuzzy Systems, Calcutta, India. Lecture Notes in Artificial Intelligence. 2275:2002;1-11 Springer, Berlin.
    • (2002) Lecture Notes in Artificial Intelligence , vol.2275 , pp. 1-11
    • Dubois, D.1    Prade, H.2    Ughetto, L.3
  • 36
    • 0027242497 scopus 로고
    • A statistical decision rule with incomplete knowledge about classes
    • Dubuisson B., Masson M. A statistical decision rule with incomplete knowledge about classes. Pattern Recognition. 26:(1):1993;155-165.
    • (1993) Pattern Recognition , vol.26 , Issue.1 , pp. 155-165
    • Dubuisson, B.1    Masson, M.2
  • 37
    • 0016939390 scopus 로고
    • The distance-weighted k-nearest-neighbor rule
    • Dudani S.A. The distance-weighted k-nearest-neighbor rule. IEEE Trans. Systems Man Cybernet. 6:(4):1976;325-327.
    • (1976) IEEE Trans. Systems Man Cybernet. , vol.6 , Issue.4 , pp. 325-327
    • Dudani, S.A.1
  • 38
    • 0040491083 scopus 로고
    • Discriminatory analysis: Nonparametric discrimination: Consistency principles
    • B.V. Dasarathy. Los Alamitos, CA: IEEE Computer Society Press. Reprint of original work from 1951
    • Fix E., Hodges J.L. Discriminatory analysis: nonparametric discrimination: consistency principles. Dasarathy B.V. Nearest Neighbor (NN) Norms: NN Pattern Classification Techniques. 1991;IEEE Computer Society Press, Los Alamitos, CA. Reprint of original work from 1951.
    • (1991) Nearest Neighbor (NN) Norms: NN Pattern Classification Techniques
    • Fix, E.1    Hodges, J.L.2
  • 39
    • 0040491083 scopus 로고
    • Discriminatory analysis: Nonparametric discrimination: Small sample performance
    • B.V. Dasarathy. Los Alamitos, CA: IEEE Computer Society Press. Reprint of original work from 1952
    • Fix E., Hodges J.L. Discriminatory analysis: Nonparametric discrimination: Small sample performance. Dasarathy B.V. Nearest Neighbor (NN) Norms: NN Pattern Classification Techniques. 1991;IEEE Computer Society Press, Los Alamitos, CA. Reprint of original work from 1952.
    • (1991) Nearest Neighbor (NN) Norms: NN Pattern Classification Techniques
    • Fix, E.1    Hodges, J.L.2
  • 41
    • 84931162639 scopus 로고
    • The condensed nearest neighbor rule
    • Hart P.E. The condensed nearest neighbor rule. IEEE Trans. Inform. Theory. 14:1968;515-516.
    • (1968) IEEE Trans. Inform. Theory , vol.14 , pp. 515-516
    • Hart, P.E.1
  • 42
    • 0014818402 scopus 로고
    • The nearest neighbor classification rule with a reject option
    • Hellman M.E. The nearest neighbor classification rule with a reject option. IEEE Trans. Systems Man Cybernet. 6:1970;179-185.
    • (1970) IEEE Trans. Systems Man Cybernet. , vol.6 , pp. 179-185
    • Hellman, M.E.1
  • 43
    • 4244031157 scopus 로고    scopus 로고
    • Toward a probabilistic formalization of case-based inference
    • T. Dean. Stockholm, Sweden, San Mateo, CA: Morgan Kaufmann
    • Hüllermeier E. Toward a probabilistic formalization of case-based inference. Dean T. Proc. IJCAI-99, Stockholm, Sweden. 1999;248-253 Morgan Kaufmann, San Mateo, CA.
    • (1999) Proc. IJCAI-99 , pp. 248-253
    • Hüllermeier, E.1
  • 44
    • 4243930007 scopus 로고    scopus 로고
    • On the representation and combination of evidence in instance-based learning
    • 15th European Conference on Artificial Intelligence, Lyon, France, Amsterdam: IOS Press
    • Hüllermeier E. On the representation and combination of evidence in instance-based learning. Proc. ECAI-2002, 15th European Conference on Artificial Intelligence, Lyon, France. 2002;360-364 IOS Press, Amsterdam.
    • (2002) Proc. ECAI-2002 , pp. 360-364
    • Hüllermeier, E.1
  • 46
    • 0000941048 scopus 로고
    • A learning scheme for a fuzzy k-NN rule
    • Józwik A. A learning scheme for a fuzzy k-NN rule. Pattern Recognition Lett. 1:1983;287-289.
    • (1983) Pattern Recognition Lett. , vol.1 , pp. 287-289
    • Józwik, A.1
  • 48
    • 0001892558 scopus 로고
    • Instance-based prediction of real-valued attributes
    • Kibler D., Aha D.W. Instance-based prediction of real-valued attributes. Comput. Intelligence. 5:1989;51-57.
    • (1989) Comput. Intelligence , vol.5 , pp. 51-57
    • Kibler, D.1    Aha, D.W.2
  • 49
    • 0022806091 scopus 로고
    • A fast k nearest neighbor finding algorithm based on the ordered partition
    • Kim B.S., Park S.B. A fast k nearest neighbor finding algorithm based on the ordered partition. IEEE Trans. Pattern Analysis and Machine Intelligence. 8:(6):1985;761-766.
    • (1985) IEEE Trans. Pattern Analysis and Machine Intelligence , vol.8 , Issue.6 , pp. 761-766
    • Kim, B.S.1    Park, S.B.2
  • 52
    • 0011647002 scopus 로고
    • Counterfactuals and comparative possibility
    • Lewis D.K. Counterfactuals and comparative possibility. J. Philos. Logic. 2:1973.
    • (1973) J. Philos. Logic , vol.2
    • Lewis, D.K.1
  • 53
    • 0001681560 scopus 로고
    • A nonparametric estimate of a multivariate density function
    • Loftsgaarden D.O., Quesenberry C.P. A nonparametric estimate of a multivariate density function. Ann. Math. Stat. 36:1965;1049-1051.
    • (1965) Ann. Math. Stat. , vol.36 , pp. 1049-1051
    • Loftsgaarden, D.O.1    Quesenberry, C.P.2
  • 54
    • 0023211620 scopus 로고
    • A re-examination of the distance-weighted k-nearest neighbor classification rule
    • Macleod J., Lik A., Titterington D. A re-examination of the distance-weighted k-nearest neighbor classification rule. IEEE Trans. Systems Man Cybernet. 17:(4):1987;689-696.
    • (1987) IEEE Trans. Systems Man Cybernet. , vol.17 , Issue.4 , pp. 689-696
    • Macleod, J.1    Lik, A.2    Titterington, D.3
  • 56
    • 0003682772 scopus 로고
    • The need for biases in learning generalizations
    • Rutgers University, New Brunswick, NJ
    • T.M. Mitchell, The need for biases in learning generalizations, Technical Report TR CBM-TR-117, Rutgers University, New Brunswick, NJ, 1980.
    • (1980) Technical Report , vol.TR CBM-TR-117
    • Mitchell, T.M.1
  • 57
    • 0000780982 scopus 로고
    • Analogy and similarity in scientific reasoning
    • D.H. Helman. Dordrecht: Kluwer Academic
    • Niiniluoto I. Analogy and similarity in scientific reasoning. Helman D.H. Analogical Reasoning. 1988;271-298 Kluwer Academic, Dordrecht.
    • (1988) Analogical Reasoning , pp. 271-298
    • Niiniluoto, I.1
  • 59
    • 0001473437 scopus 로고
    • On estimation of a probability density function and mode
    • Parzen E. On estimation of a probability density function and mode. Ann. Math. Statist. 33:1962;1065-1076.
    • (1962) Ann. Math. Statist. , vol.33 , pp. 1065-1076
    • Parzen, E.1
  • 60
    • 0038136319 scopus 로고
    • A generalized k-nearest neighbor rule
    • Patrick E.A., Fischer F.P. A generalized k-nearest neighbor rule. Inform. and Control. 16:(2):1970;128-152.
    • (1970) Inform. and Control , vol.16 , Issue.2 , pp. 128-152
    • Patrick, E.A.1    Fischer, F.P.2
  • 62
    • 85144600007 scopus 로고
    • Combining instance-based and model-based learning
    • San Mateo, CA: Morgan Kaufmann
    • Quinlan R. Combining instance-based and model-based learning. Proc. 10th International Conference of Machine Learning. 1993;236-243 Morgan Kaufmann, San Mateo, CA.
    • (1993) Proc. 10th International Conference of Machine Learning , pp. 236-243
    • Quinlan, R.1
  • 63
    • 0001529784 scopus 로고
    • Remarks on some nonparametric estimates of a density function
    • Rosenblatt M. Remarks on some nonparametric estimates of a density function. Ann. Math. Statist. 27:1956;832-837.
    • (1956) Ann. Math. Statist. , vol.27 , pp. 832-837
    • Rosenblatt, M.1
  • 64
    • 0026156490 scopus 로고
    • A nearest hyperrectangle learning method
    • Salzberg S. A nearest hyperrectangle learning method. Machine Learning. 6:1991;251-276.
    • (1991) Machine Learning , vol.6 , pp. 251-276
    • Salzberg, S.1
  • 65
    • 0042143697 scopus 로고
    • On possibility qualification in natural languages
    • Sanchez E. On possibility qualification in natural languages. Inform. Sci. 15:1978;45-76.
    • (1978) Inform. Sci. , vol.15 , pp. 45-76
    • Sanchez, E.1
  • 67
    • 0014432211 scopus 로고
    • A two-dimensional interpolation function for irregularly spaced data
    • Shepard D. A two-dimensional interpolation function for irregularly spaced data. Proc. 23rd National Conference of the ACM. 1968;517-523.
    • (1968) Proc. 23rd National Conference of the ACM , pp. 517-523
    • Shepard, D.1
  • 70
    • 0022909661 scopus 로고
    • Toward memory-based reasoning
    • Stanfill C., Waltz D. Toward memory-based reasoning. Comm. ACM. 1986;1213-1228.
    • (1986) Comm. ACM , pp. 1213-1228
    • Stanfill, C.1    Waltz, D.2
  • 71
    • 0027682298 scopus 로고
    • Cost-sensitive learning of classification knowledge and its application to robotics
    • Tan M. Cost-sensitive learning of classification knowledge and its application to robotics. Machine Learning. 13:(7):1993;7-34.
    • (1993) Machine Learning , vol.13 , Issue.7 , pp. 7-34
    • Tan, M.1
  • 75
    • 0005873104 scopus 로고    scopus 로고
    • A new approach to fuzzy reasoning
    • Weisbrod J. A new approach to fuzzy reasoning. Soft Comput. 2:1998;89-99.
    • (1998) Soft Comput. , vol.2 , pp. 89-99
    • Weisbrod, J.1
  • 76
    • 84973608347 scopus 로고
    • Using k-d trees to improve the retrieval step in case-based reasoning
    • S. Wess, K.D. Althoff, & M.M. Richter. Berlin: Springer
    • Wess S., Althoff K.D., Derwand G. Using k-d trees to improve the retrieval step in case-based reasoning. Wess S., Althoff K.D., Richter M.M. Topics in Case-Based Reasoning. 1994;167-181 Springer, Berlin.
    • (1994) Topics in Case-Based Reasoning , pp. 167-181
    • Wess, S.1    Althoff, K.D.2    Derwand, G.3
  • 77
    • 0031073477 scopus 로고    scopus 로고
    • A review and empirical comparison of feature weighting methods for a class of lazy learning algorithms
    • Wettschereck D., Aha D.W., Mohri T. A review and empirical comparison of feature weighting methods for a class of lazy learning algorithms. AI Rev. 11:1997;273-314.
    • (1997) AI Rev. , vol.11 , pp. 273-314
    • Wettschereck, D.1    Aha, D.W.2    Mohri, T.3
  • 78
    • 0015361129 scopus 로고
    • Asymptotic properties of nearest neighbor rules using edited data
    • Wilson D.L. Asymptotic properties of nearest neighbor rules using edited data. IEEE Trans. Systems Man Cybernet. 2:(3):1972;408-421.
    • (1972) IEEE Trans. Systems Man Cybernet. , vol.2 , Issue.3 , pp. 408-421
    • Wilson, D.L.1
  • 79
    • 0003471519 scopus 로고    scopus 로고
    • PhD Thesis, Department of Computer Science, Brigham Young University, Provo, UT
    • D.R. Wilson, Advances in instance-based learning algorithms, PhD Thesis, Department of Computer Science, Brigham Young University, Provo, UT, 1997.
    • (1997) Advances in Instance-based Learning Algorithms
    • Wilson, D.R.1
  • 81
    • 0017007427 scopus 로고
    • A technique to identify nearest neighbors
    • Yunck T.P. A technique to identify nearest neighbors. IEEE Trans. Systems Man Cybernet. 6:(10):1976;678-683.
    • (1976) IEEE Trans. Systems Man Cybernet. , vol.6 , Issue.10 , pp. 678-683
    • Yunck, T.P.1
  • 82
    • 49349133217 scopus 로고
    • Fuzzy sets as a basis for a theory of possibility
    • Zadeh L.A. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems. 1:1978;3-28.
    • (1978) Fuzzy Sets and Systems , vol.1 , pp. 3-28
    • Zadeh, L.A.1
  • 83
    • 0017985349 scopus 로고
    • PRUF: A meaning representation language for natural language
    • Zadeh L.A. PRUF: A meaning representation language for natural language. Internat. J. Man-Machine Stud. 10:1978;395-460.
    • (1978) Internat. J. Man-Machine Stud. , vol.10 , pp. 395-460
    • Zadeh, L.A.1
  • 84
    • 1642469977 scopus 로고    scopus 로고
    • Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic
    • Zadeh L.A. Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets and Systems. 90:(2):1997;111-127.
    • (1997) Fuzzy Sets and Systems , vol.90 , Issue.2 , pp. 111-127
    • Zadeh, L.A.1
  • 86
    • 0031069120 scopus 로고    scopus 로고
    • Intelligent selection of instances for prediction in lazy learning algorithms
    • Zhang J., Yim Y., Yang J. Intelligent selection of instances for prediction in lazy learning algorithms. Artificial Intelligence Rev. 11:1997;175-191.
    • (1997) Artificial Intelligence Rev. , vol.11 , pp. 175-191
    • Zhang, J.1    Yim, Y.2    Yang, J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.