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Volumn 5572 LNAI, Issue , 2009, Pages 589-596

Feature construction and feature selection in presence of attribute interactions

Author keywords

Data reduction; Feature construction; Genetic algorithms

Indexed keywords

ATTRIBUTE INTERACTIONS; EMPIRICAL STUDIES; FEATURE CONSTRUCTION; FEATURE SELECTION; LEARNING ACCURACY; LEARNING DIFFICULTIES; PREDICTIVE ACCURACY; TARGET CONCEPT;

EID: 70350658296     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-02319-4_71     Document Type: Conference Paper
Times cited : (8)

References (20)
  • 2
    • 70350629262 scopus 로고    scopus 로고
    • Computational Methods of Feature Selection
    • Liu, H, Motoda, H, eds, Chapman & Hall/CRC, Boca Raton
    • Liu, H., Motoda, H. (eds.): Computational Methods of Feature Selection. Data Mining and Knowledge Discovery Series. Chapman & Hall/CRC, Boca Raton (2007)
    • (2007) Data Mining and Knowledge Discovery Series
  • 3
    • 38349047852 scopus 로고    scopus 로고
    • Fitness function comparison for GA-based feature construction
    • Borrajo, D, Castillo, L, Corchado, J.M, eds, CAEPIA 2007, Springer, Heidelberg
    • Shafti, L.S., Pérez, E.: Fitness function comparison for GA-based feature construction. In: Borrajo, D., Castillo, L., Corchado, J.M. (eds.) CAEPIA 2007. LNCS, vol. 4788, pp. 249-258. Springer, Heidelberg (2007)
    • (2007) LNCS , vol.4788 , pp. 249-258
    • Shafti, L.S.1    Pérez, E.2
  • 4
    • 55349113637 scopus 로고    scopus 로고
    • Data reduction by genetic algorithms and non-algebraic feature construction: A case study
    • Shafti, L.S., Pérez, E.: Data reduction by genetic algorithms and non-algebraic feature construction: A case study. In: Proceedings of HIS (2008)
    • (2008) Proceedings of HIS
    • Shafti, L.S.1    Pérez, E.2
  • 6
    • 0027580356 scopus 로고
    • Very simple classification rules perform well on most commonly used datasets
    • Holte, R.C.: Very simple classification rules perform well on most commonly used datasets. Machine Learning 11, 63-91 (1993)
    • (1993) Machine Learning , vol.11 , pp. 63-91
    • Holte, R.C.1
  • 7
    • 0242370859 scopus 로고    scopus 로고
    • Jakulin, A., Bratko, I., et al.: Attribute interactions in medical data analysis. In: Dojat, M., Keravnou, E.T., Barahona, P. (eds.) AIME 2003. LNCS, 2780, pp. 229-238. Springer, Heidelberg (2003)
    • Jakulin, A., Bratko, I., et al.: Attribute interactions in medical data analysis. In: Dojat, M., Keravnou, E.T., Barahona, P. (eds.) AIME 2003. LNCS, vol. 2780, pp. 229-238. Springer, Heidelberg (2003)
  • 8
    • 85152623456 scopus 로고
    • Small disjuncts in action: Learning to diagnose errors in the local loop of the telephone network
    • Danyluk, A.P., Provost, F.J.: Small disjuncts in action: Learning to diagnose errors in the local loop of the telephone network. In: Proceedings of ICML (1993)
    • (1993) Proceedings of ICML
    • Danyluk, A.P.1    Provost, F.J.2
  • 9
    • 0000686085 scopus 로고
    • Learning hard concepts through constructive induction: Framework and rationale
    • Rendell, L.A., Seshu, R.: Learning hard concepts through constructive induction: Framework and rationale. Computational Intelligence 6, 247-270 (1990)
    • (1990) Computational Intelligence , vol.6 , pp. 247-270
    • Rendell, L.A.1    Seshu, R.2
  • 10
    • 0035500276 scopus 로고    scopus 로고
    • Understanding the crucial role of attribute interaction in data mining
    • Freitas, A.A.: Understanding the crucial role of attribute interaction in data mining. Artificial Intelligence Review 16(3), 177-199 (2001)
    • (2001) Artificial Intelligence Review , vol.16 , Issue.3 , pp. 177-199
    • Freitas, A.A.1
  • 11
    • 84880853409 scopus 로고    scopus 로고
    • Searching for interacting features
    • Veloso, M.M, ed, Hyderabad, India, pp, January
    • Zhao, Z., Liu, H.: Searching for interacting features. In: Veloso, M.M. (ed.) Proceedings of IJCAI, Hyderabad, India, pp. 1156-1161 (January 2007)
    • (2007) Proceedings of IJCAI , pp. 1156-1161
    • Zhao, Z.1    Liu, H.2
  • 13
    • 0008087071 scopus 로고
    • Pattern recognition as knowledge-guided computer induction
    • Technical Report 927, Dept. of Computer Science, University of Illinois
    • Michalski, R.S.: Pattern recognition as knowledge-guided computer induction. Technical Report 927, Dept. of Computer Science, University of Illinois (1978)
    • (1978)
    • Michalski, R.S.1
  • 14
    • 70350674634 scopus 로고    scopus 로고
    • Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufmann, San Francisco (1993)
    • Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufmann, San Francisco (1993)
  • 15
    • 0032028849 scopus 로고    scopus 로고
    • Feature space transformation using genetic algorithms
    • Vafaie, H., DeJong, K.: Feature space transformation using genetic algorithms. IEEE Intelligent Systems 13(2), 57-65 (1998)
    • (1998) IEEE Intelligent Systems , vol.13 , Issue.2 , pp. 57-65
    • Vafaie, H.1    DeJong, K.2
  • 16
    • 0008814745 scopus 로고
    • Using multidimensional projection to find relations
    • Morgan Kaufmann, San Francisco
    • Pérez, E., Rendell, L.A.: Using multidimensional projection to find relations. In: Proceedings of the Twelfth ICML, pp. 447-455. Morgan Kaufmann, San Francisco (1995)
    • (1995) Proceedings of the Twelfth ICML , pp. 447-455
    • Pérez, E.1    Rendell, L.A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.