메뉴 건너뛰기




Volumn 36, Issue 7, 2009, Pages 10494-10502

Extracting rules for classification problems: AIS based approach

Author keywords

Artificial Immune Systems; Hybrid neural networks; Opt aiNET; Optimization; Rule extraction

Indexed keywords

ARTIFICIAL IMMUNE SYSTEMS; ARTIFICIAL NEURAL NETWORKS; CLASSIFICATION ACCURACIES; CLEVELAND; DATA MINING APPLICATIONS; DATA-SETS; EXTRACTING RULES; HEART DISEASE; HEPATITIS DATASET; HYBRID NEURAL NETWORKS; MACHINE LEARNING REPOSITORIES; OPT-AINET; RULE EXTRACTION; UNIVERSITY OF CALIFORNIA; WEB SITES;

EID: 67349236666     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2009.01.029     Document Type: Article
Times cited : (41)

References (47)
  • 1
    • 0000138466 scopus 로고
    • Template-based algorithm for connectionist rule extraction
    • Tesauro G., Touetzky D., and Leen T. (Eds), MIT Press, Cambridge, MA
    • Alexander J.A., and Mozer M.C. Template-based algorithm for connectionist rule extraction. In: Tesauro G., Touetzky D., and Leen T. (Eds). Advances in neural information processing systems Vol. 7 (1995), MIT Press, Cambridge, MA
    • (1995) Advances in neural information processing systems , vol.7
    • Alexander, J.A.1    Mozer, M.C.2
  • 2
    • 0029484103 scopus 로고    scopus 로고
    • A survey and critique of techniques for extracting rules from trained Artificial Neural Networks
    • Andrews R., Diederich J., and Tickle A.B. A survey and critique of techniques for extracting rules from trained Artificial Neural Networks. Knowledge-Based Systems 8 (1996) 373-389
    • (1996) Knowledge-Based Systems , vol.8 , pp. 373-389
    • Andrews, R.1    Diederich, J.2    Tickle, A.B.3
  • 3
    • 67349256670 scopus 로고    scopus 로고
    • Baron (1994). Knowledge extraction from neural networks: A survey. In: Report No. 94-17, Laboratoire de l'Informatique du Paralle'lisme, Ecole Normale Supe'rieure de Lyon.
    • Baron (1994). Knowledge extraction from neural networks: A survey. In: Report No. 94-17, Laboratoire de l'Informatique du Paralle'lisme, Ecole Normale Supe'rieure de Lyon.
  • 5
    • 0031915593 scopus 로고    scopus 로고
    • Dynamic on-line clustering and state extraction: An approach to symbolic learning
    • Das S., and Mozer M. Dynamic on-line clustering and state extraction: An approach to symbolic learning. Neural Networks 11 1 (1998) 53-64
    • (1998) Neural Networks , vol.11 , Issue.1 , pp. 53-64
    • Das, S.1    Mozer, M.2
  • 6
    • 33749074288 scopus 로고    scopus 로고
    • MLP-based equalization and pre-distortion using an artificial immune network. Machine learning for signal processing, 2005
    • de Attux, R. R., Duarte, L. T., Ferrari, R., Panazio, C. M., de Castro, L. N., Von Zuben, F. J., et al. (2005). MLP-based equalization and pre-distortion using an artificial immune network. Machine learning for signal processing, 2005. IEEE workshop (pp. 177-182).
    • (2005) IEEE workshop , pp. 177-182
    • de Attux, R.R.1    Duarte, L.T.2    Ferrari, R.3    Panazio, C.M.4    de Castro, L.N.5    Von Zuben, F.J.6
  • 9
    • 0141578371 scopus 로고    scopus 로고
    • A new methodology of extraction, optimization and application of crisp and fuzzy logical rules
    • Duch W., Adamczak R., and Grabczwski K. A new methodology of extraction, optimization and application of crisp and fuzzy logical rules. IEEE Transactions on Neural Networks 11 2 (2000) 1-31
    • (2000) IEEE Transactions on Neural Networks , vol.11 , Issue.2 , pp. 1-31
    • Duch, W.1    Adamczak, R.2    Grabczwski, K.3
  • 10
    • 2442617148 scopus 로고    scopus 로고
    • Extracting rules from trained neural network using GA for managing E-business
    • Elalfi, A. E., Haque, R., & Elalami, M. E. (2004). Extracting rules from trained neural network using GA for managing E-business. Applied Soft Computing, 4.
    • (2004) Applied Soft Computing , vol.4
    • Elalfi, A.E.1    Haque, R.2    Elalami, M.E.3
  • 11
    • 0023962833 scopus 로고
    • Connection expert systems
    • Gallant S.I. Connection expert systems. Communications of the ACM 31 2 (1988) 152-169
    • (1988) Communications of the ACM , vol.31 , Issue.2 , pp. 152-169
    • Gallant, S.I.1
  • 12
    • 0035127989 scopus 로고    scopus 로고
    • Symbolic knowledge extraction from trained neural networks: A sound approach
    • Garcez A.S.D., Broda K., and Gabbay D.M. Symbolic knowledge extraction from trained neural networks: A sound approach. Applied Intelligence 125 (2001) 155-207
    • (2001) Applied Intelligence , vol.125 , pp. 155-207
    • Garcez, A.S.D.1    Broda, K.2    Gabbay, D.M.3
  • 13
    • 34248651234 scopus 로고    scopus 로고
    • Using neural networks and immune algorithms to find the optimal parameters for an IC wire bonding process
    • Hou T., Su C., and Chang H. Using neural networks and immune algorithms to find the optimal parameters for an IC wire bonding process. Expert System with Applications 34 (2008) 427-436
    • (2008) Expert System with Applications , vol.34 , pp. 427-436
    • Hou, T.1    Su, C.2    Chang, H.3
  • 14
    • 33750967077 scopus 로고    scopus 로고
    • Extracting rules from multilayer perceptrons in classification problems: A clustering-based approach
    • Hruschka E.R., and Ebecken N.F.F. Extracting rules from multilayer perceptrons in classification problems: A clustering-based approach. Neurocomputing 70 (2006) 384-397
    • (2006) Neurocomputing , vol.70 , pp. 384-397
    • Hruschka, E.R.1    Ebecken, N.F.F.2
  • 15
    • 67349212054 scopus 로고    scopus 로고
    • Last Accessed March 2008
    • . Last Accessed March 2008.
  • 16
    • 0036888743 scopus 로고    scopus 로고
    • Extract intelligible and concise fuzzy rules from neural networks
    • Huang S.H., and Xing H. Extract intelligible and concise fuzzy rules from neural networks. Fuzzy Sets and Systems 132 (2002) 233-243
    • (2002) Fuzzy Sets and Systems , vol.132 , pp. 233-243
    • Huang, S.H.1    Xing, H.2
  • 19
    • 44949105491 scopus 로고    scopus 로고
    • Design of a hybrid system for the diabetes and heart diseases
    • Kahramanli H., and Allahverdi N. Design of a hybrid system for the diabetes and heart diseases. Expert Systems with Applications 35 1-2 (2008) 82-89
    • (2008) Expert Systems with Applications , vol.35 , Issue.1-2 , pp. 82-89
    • Kahramanli, H.1    Allahverdi, N.2
  • 23
    • 33744804263 scopus 로고    scopus 로고
    • Psychoclonal algorithm based approach to solve continuous flow shop scheduling problem
    • Kumar A., Prakash A., Shankar R., and Tiwari M.K. Psychoclonal algorithm based approach to solve continuous flow shop scheduling problem. Expert System with Applications 31 (2006) 504-514
    • (2006) Expert System with Applications , vol.31 , pp. 504-514
    • Kumar, A.1    Prakash, A.2    Shankar, R.3    Tiwari, M.K.4
  • 24
    • 28244463200 scopus 로고    scopus 로고
    • Accurate and reliable diagnosis and classification using probabilistic ensemble simplified fuzzy ARTMAP
    • Loo C.K. Accurate and reliable diagnosis and classification using probabilistic ensemble simplified fuzzy ARTMAP. IEEE Transactions on Knowledge and Data Engineering 17 11 (2005)
    • (2005) IEEE Transactions on Knowledge and Data Engineering , vol.17 , Issue.11
    • Loo, C.K.1
  • 27
    • 0000246504 scopus 로고
    • Rule induction through integrated symbolic and subsymbolic processing
    • Moody J.E., Hanson S.J., and Lippmann R.P. (Eds), Morgan Kaufmann Publishers, Los Allos
    • McMillan M.C., Mozer P., and Smolenski P. Rule induction through integrated symbolic and subsymbolic processing. In: Moody J.E., Hanson S.J., and Lippmann R.P. (Eds). Advances in Neural Processing Systems Vol. IV (1992), Morgan Kaufmann Publishers, Los Allos 969-976
    • (1992) Advances in Neural Processing Systems , vol.IV , pp. 969-976
    • McMillan, M.C.1    Mozer, P.2    Smolenski, P.3
  • 28
    • 38349177924 scopus 로고    scopus 로고
    • Data mining with a simulated annealing based fuzzy classification system
    • Mohamadi H., Habibi J., Abadeh M.S., and Sadi H. Data mining with a simulated annealing based fuzzy classification system. Pattern Recognition 41 (2008) 1824-1833
    • (2008) Pattern Recognition , vol.41 , pp. 1824-1833
    • Mohamadi, H.1    Habibi, J.2    Abadeh, M.S.3    Sadi, H.4
  • 29
    • 84890336863 scopus 로고    scopus 로고
    • A comparative study of genetic sequence classification algorithms, Neural Networks for Signal Processing
    • September, pp
    • Mukhopadhyay, S., Tang, C., Huang, J., Yu, M., & Palakal, M. (2002). A comparative study of genetic sequence classification algorithms, Neural Networks for Signal Processing. In Proceedings of the 2002 12th IEEE workshop on 4-6 September, (pp. 57-66).
    • (2002) Proceedings of the 2002 12th IEEE workshop on 4-6 , pp. 57-66
    • Mukhopadhyay, S.1    Tang, C.2    Huang, J.3    Yu, M.4    Palakal, M.5
  • 32
    • 33745834241 scopus 로고    scopus 로고
    • Irvine, CA: University of California, Department of Information and Computer Science, Last Accessed January 2007
    • Newman, D. J., Hettich, S., Blake, C. L., & Merz, C. J., (1998). UCI Repository of machine learning databases. Irvine, CA: University of California, Department of Information and Computer Science. . (Last Accessed January 2007).
    • (1998) UCI Repository of machine learning databases
    • Newman, D.J.1    Hettich, S.2    Blake, C.L.3    Merz, C.J.4
  • 33
    • 51049095878 scopus 로고    scopus 로고
    • Greedy rule generation from discrete data and its use in neural network rule extraction
    • 10.1016/j.neunet.2008.01.003
    • Odajima K., Hayashi Y., Tianxia G., and Setiono R. Greedy rule generation from discrete data and its use in neural network rule extraction. Neural Networks (2008) 10.1016/j.neunet.2008.01.003
    • (2008) Neural Networks
    • Odajima, K.1    Hayashi, Y.2    Tianxia, G.3    Setiono, R.4
  • 35
    • 33845679519 scopus 로고    scopus 로고
    • Neural network explanation using inversion
    • Saad E.W., and Wunsch D.C.I. Neural network explanation using inversion. Neural Networks 20 (2007) 78-93
    • (2007) Neural Networks , vol.20 , pp. 78-93
    • Saad, E.W.1    Wunsch, D.C.I.2
  • 36
    • 33846588283 scopus 로고    scopus 로고
    • Anomaly detection in TCP/IP networks using immune systems paradigm
    • Seredynski F., and Bouvry P. Anomaly detection in TCP/IP networks using immune systems paradigm. Computer Communications 30 (2007) 740-749
    • (2007) Computer Communications , vol.30 , pp. 740-749
    • Seredynski, F.1    Bouvry, P.2
  • 37
    • 56349135978 scopus 로고    scopus 로고
    • Multi-valued logic mapping of neurons in feedforward networks
    • Sethi I., and Yoo J. Multi-valued logic mapping of neurons in feedforward networks. Engineering Intelligent Systems 4 4 (1996) 153-243
    • (1996) Engineering Intelligent Systems , vol.4 , Issue.4 , pp. 153-243
    • Sethi, I.1    Yoo, J.2
  • 38
    • 0033885056 scopus 로고    scopus 로고
    • FERNN: An algorithm for fast extraction of rules from neural networks
    • Setiono R., and Leow K. FERNN: An algorithm for fast extraction of rules from neural networks. Applied Intelligence 12 1-2 (2000) 15-25
    • (2000) Applied Intelligence , vol.12 , Issue.1-2 , pp. 15-25
    • Setiono, R.1    Leow, K.2
  • 39
    • 0036565303 scopus 로고    scopus 로고
    • Extraction of rules from artificial neural networks for nonlinear regression
    • Setiono R., Leow W.K., and Zuarada J.M. Extraction of rules from artificial neural networks for nonlinear regression. IEEE Transactions on Neural Networks 13 3 (2002) 564-577
    • (2002) IEEE Transactions on Neural Networks , vol.13 , Issue.3 , pp. 564-577
    • Setiono, R.1    Leow, W.K.2    Zuarada, J.M.3
  • 40
    • 0026927202 scopus 로고
    • Fuzzy min-max neural networks. Part 1. Classification
    • Simpson P. Fuzzy min-max neural networks. Part 1. Classification. IEEE Transactions on Neural Networks 3 (1992) 776-786
    • (1992) IEEE Transactions on Neural Networks , vol.3 , pp. 776-786
    • Simpson, P.1
  • 43
    • 35048865866 scopus 로고    scopus 로고
    • A comment on Opt-aiNET: An immune network algorithm for optimization
    • Genetic and Evolutionary Computation. Kalyanmoy D., et al. (Ed), Springer
    • Timmis J., and Edmonds C. A comment on Opt-aiNET: An immune network algorithm for optimization. In: Kalyanmoy D., et al. (Ed). Genetic and Evolutionary Computation. Lecture Notes in Computer Science Vol. 3102 (2004), Springer 308-317
    • (2004) Lecture Notes in Computer Science , vol.3102 , pp. 308-317
    • Timmis, J.1    Edmonds, C.2
  • 44
    • 0027678679 scopus 로고
    • Extracting refined rules from knowledge-based neural networks
    • Towell G.G., and Shavlik J. Extracting refined rules from knowledge-based neural networks. Machine Learning 13 (1993) 71-101
    • (1993) Machine Learning , vol.13 , pp. 71-101
    • Towell, G.G.1    Shavlik, J.2
  • 45
    • 13544277431 scopus 로고    scopus 로고
    • Classification with incomplete survey data: A Hopfield neural network approach
    • Wang S. Classification with incomplete survey data: A Hopfield neural network approach. Computers and Operations Research 32 (2005) 2583-1594
    • (2005) Computers and Operations Research , vol.32 , pp. 2583-1594
    • Wang, S.1
  • 46
    • 67349209814 scopus 로고    scopus 로고
    • Weijters, T., Bosh, A. V. D., Herik, J. V. D. (1997). Intelligible neural networks with BP-SOM. In: Proceedings of the ninth dutch conference on artificial intelligence. (pp. 27-36).
    • Weijters, T., Bosh, A. V. D., Herik, J. V. D. (1997). Intelligible neural networks with BP-SOM. In: Proceedings of the ninth dutch conference on artificial intelligence. (pp. 27-36).
  • 47
    • 4444290554 scopus 로고    scopus 로고
    • Learning to detect texture objects by artificial immune approaches
    • Zheng H., Zhang J., and Nahavandi S. Learning to detect texture objects by artificial immune approaches. Future Generation Computer Systems 20 (2004) 1197-1208
    • (2004) Future Generation Computer Systems , vol.20 , pp. 1197-1208
    • Zheng, H.1    Zhang, J.2    Nahavandi, S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.