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Volumn 8073 LNAI, Issue , 2013, Pages 629-638

Noisy data set identification

Author keywords

Data Complexity Measures; Noise identification; Noisy data

Indexed keywords

DATA COLLECTION; DATA COMPLEXITY; DATA SET; LEARNING PROCESS; MACHINE LEARNING MODELS; NOISE IDENTIFICATION; NOISY DATA; TRAINING TIME;

EID: 84884954199     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-40846-5_63     Document Type: Conference Paper
Times cited : (21)

References (26)
  • 4
    • 33744584654 scopus 로고
    • Induction of decision trees
    • Quinlan, J.R.: Induction of decision trees. Machine Learning 1(1), 81-106 (1986)
    • (1986) Machine Learning , vol.1 , Issue.1 , pp. 81-106
    • Quinlan, J.R.1
  • 5
    • 0001182408 scopus 로고
    • The effect of noise on concept learning
    • Michalski, R.S.I., Carboneel, J.G., Mitchell (eds.) Morgan Kaufmann Publishers Inc.
    • Quinlan, J.R.: The effect of noise on concept learning. In: Michalski, R.S.I., Carboneel, J.G., Mitchell (eds.) Machine Learning. Morgan Kaufmann Publishers Inc. (1986)
    • (1986) Machine Learning
    • Quinlan, J.R.1
  • 6
    • 11344280625 scopus 로고    scopus 로고
    • Evaluation of noise reduction techniques in the splice junction recognition problem
    • Lorena, A.C., Carvalho, A.C.P.L.F.: Evaluation of noise reduction techniques in the splice junction recognition problem. Genetics and Molecular Biology 27(4), 665-672 (2004)
    • (2004) Genetics and Molecular Biology , vol.27 , Issue.4 , pp. 665-672
    • Lorena, A.C.1    Carvalho, A.C.P.L.F.2
  • 7
    • 0031144150 scopus 로고    scopus 로고
    • Data quality in context
    • Strong, D.M., Lee, Y.W., Wang, R.Y.: Data quality in context. Commun. ACM 40(5), 103-110 (1997)
    • (1997) Commun. ACM , vol.40 , Issue.5 , pp. 103-110
    • Strong, D.M.1    Lee, Y.W.2    Wang, R.Y.3
  • 8
    • 0034143132 scopus 로고    scopus 로고
    • Noise detection and elimination in data proprocessing: Experiments in medical domains
    • Gamberger, D., Lavrac, N., Dzeroski, S.: Noise detection and elimination in data proprocessing: Experiments in medical domains. Applied Artificial Intelligence 14(2), 205-223 (2000)
    • (2000) Applied Artificial Intelligence , vol.14 , Issue.2 , pp. 205-223
    • Gamberger, D.1    Lavrac, N.2    Dzeroski, S.3
  • 9
    • 33747739087 scopus 로고
    • Robust decision trees: Removing outliers from databases
    • John, G.H.: Robust decision trees: Removing outliers from databases. In: KDD, pp. 174-179 (1995)
    • (1995) KDD , pp. 174-179
    • John, G.H.1
  • 10
    • 0346108359 scopus 로고
    • Using qualitative hypotheses to identify inaccurate data
    • Zhao, Q., Nishida, T.: Using qualitative hypotheses to identify inaccurate data. J. Artif. Intell. Res. (JAIR) 3, 119-145 (1995)
    • (1995) J. Artif. Intell. Res. (JAIR) , vol.3 , pp. 119-145
    • Zhao, Q.1    Nishida, T.2
  • 11
    • 0030354375 scopus 로고    scopus 로고
    • Identifying and eliminating mislabeled training instances
    • Brodley, C.E., Friedl, M.A.: Identifying and eliminating mislabeled training instances. In: AAAI/IAAI, vol. 1, pp. 799-805 (1996)
    • (1996) AAAI/IAAI , vol.1 , pp. 799-805
    • Brodley, C.E.1    Friedl, M.A.2
  • 12
    • 0343859301 scopus 로고    scopus 로고
    • Correcting noisy data
    • Teng, C.M.: Correcting noisy data. In: ICML, pp. 239-248 (1999)
    • (1999) ICML , pp. 239-248
    • Teng, C.M.1
  • 13
    • 1942484424 scopus 로고    scopus 로고
    • Eliminating class noise in large datasets
    • Zhu, X., Wu, X., Chen, Q.: Eliminating class noise in large datasets. In: ICML, pp. 920-927 (2003)
    • (2003) ICML , pp. 920-927
    • Zhu, X.1    Wu, X.2    Chen, Q.3
  • 14
    • 9444231677 scopus 로고    scopus 로고
    • Error detection and impact-sensitive instance ranking in noisy datasets
    • Zhu, X., Wu, X., Yang, Y.: Error detection and impact-sensitive instance ranking in noisy datasets. In: AAAI, pp. 378-384 (2004)
    • (2004) AAAI , pp. 378-384
    • Zhu, X.1    Wu, X.2    Yang, Y.3
  • 15
    • 0036522441 scopus 로고    scopus 로고
    • Complexity measures of supervised classification problems
    • Ho, T.K., Basu, M.: Complexity measures of supervised classification problems. IEEE Trans. Pattern Anal. Mach. Intell. 24(3), 289-300 (2002)
    • (2002) IEEE Trans. Pattern Anal. Mach. Intell. , vol.24 , Issue.3 , pp. 289-300
    • Ho, T.K.1    Basu, M.2
  • 16
    • 84866043469 scopus 로고    scopus 로고
    • Predicting noise filtering efficacy with data complexity measures for nearest neighbor classification
    • Sáez, J.A., Luengo, J., Herrera, F.: Predicting noise filtering efficacy with data complexity measures for nearest neighbor classification. Pattern Recognition 46(1), 355-364 (2013)
    • (2013) Pattern Recognition , vol.46 , Issue.1 , pp. 355-364
    • Sáez, J.A.1    Luengo, J.2    Herrera, F.3
  • 18
    • 19544372918 scopus 로고    scopus 로고
    • Class noise vs. Attribute noise: A quantitative study
    • Zhu, X., Wu, X.: Class noise vs. attribute noise: A quantitative study. Artif. Intell. Rev. 22(3), 177-210 (2004)
    • (2004) Artif. Intell. Rev. , vol.22 , Issue.3 , pp. 177-210
    • Zhu, X.1    Wu, X.2
  • 21
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • Breiman, L.: Random forests. Machine Learning 45(1), 5-32 (2001)
    • (2001) Machine Learning , vol.45 , Issue.1 , pp. 5-32
    • Breiman, L.1
  • 26
    • 29644438050 scopus 로고    scopus 로고
    • Statistical comparisons of classifiers over multiple data sets
    • Demśar, J.: Statistical comparisons of classifiers over multiple data sets. J. Mach. Learn. Res. 7, 1-30 (2006)
    • (2006) J. Mach. Learn. Res. , vol.7 , pp. 1-30
    • Demśar, J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.