메뉴 건너뛰기




Volumn 82, Issue 3, 2011, Pages 445-473

Anytime learning of anycost classifiers

Author keywords

Anytime algorithms; Cost sensitive learning; Decision trees; Resource bounded reasoning

Indexed keywords

ANYTIME ALGORITHM; ANYTIME LEARNING; COST-SENSITIVE LEARNING; DATA SETS; MEDICAL CENTER; MISCLASSIFICATION COSTS; NOVEL ALGORITHM; PREDICTIVE MODELS; RESEARCH EFFORTS; RESOURCE-BOUNDED REASONING; SINGLE PATH;

EID: 79958819318     PISSN: 08856125     EISSN: 15730565     Source Type: Journal    
DOI: 10.1007/s10994-010-5228-1     Document Type: Article
Times cited : (14)

References (60)
  • 2
    • 36948999941 scopus 로고    scopus 로고
    • University of California, Irvine, School of Information and Computer Sciences
    • Asuncion, A., & Newman, D. (2007). UCI machine learning repository. University of California, Irvine, School of Information and Computer Sciences. http://www.ics.uci.edu/~mlearn/MLRepository.html.
    • (2007) UCI Machine Learning Repository
    • Asuncion, A.1    Newman, D.2
  • 4
    • 31144459962 scopus 로고    scopus 로고
    • Integrating learning from examples into the search for diagnostic policies
    • Bayer-Zubek, V., & Dietterich, T.G. (2005). Integrating learning from examples into the search for diagnostic policies. Artificial Intelligence, 24(1), 263-303. (Pubitemid 43130938)
    • (2005) Journal of Artificial Intelligence Research , vol.24 , pp. 263-303
    • Bayer-Zubek, V.1    Dietterich, T.G.2
  • 5
    • 36348959586 scopus 로고    scopus 로고
    • VOILA: Efficient feature-value acquisition for classification
    • AAAI-07/IAAI-07 Proceedings: 22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference
    • Bilgic, M., & Getoor, L. (2007). Voila: Efficient feature-value acquisition for classification. In Proceedings of the 22nd national conference on artificial intelligence (AAAI-2007), Vancouver, British Columbia, Canada (pp. 1225-1230). (Pubitemid 350149735)
    • (2007) Proceedings of the National Conference on Artificial Intelligence , vol.2 , pp. 1225-1230
    • Bilgic, M.1    Getoor, L.2
  • 6
    • 0028447220 scopus 로고
    • Deliberation scheduling for problem solving in time-constrained environments
    • Boddy, M., & Dean, T. L. (1994). Deliberation scheduling for problem solving in time-constrained environments. Artificial Intelligence, 67(2), 245-285.
    • (1994) Artificial Intelligence , vol.67 , Issue.2 , pp. 245-285
    • Boddy, M.1    Dean, T.L.2
  • 9
    • 84957107950 scopus 로고    scopus 로고
    • Pruning Decision Trees with Misclassification Costs
    • Machine Learning: ECML-98
    • Bradford, J., Kunz, C., Kohavi, R., Brunk, C., & Brodley, C. (1998). Pruning decision trees with misclassification costs. In Proceedings of the 9th European conference on machine learning (ECML-1998), Chemnitz, Germany (pp. 131-136). (Pubitemid 128067177)
    • (1998) Lecture Notes in Computer Science , Issue.1398 , pp. 131-136
    • Bradford, J.P.1    Kunz, C.2    Kohavi, R.3    Brunk, C.4    Brodley, C.E.5
  • 12
    • 29644438050 scopus 로고    scopus 로고
    • Statistical comparisons of classifiers over multiple data sets
    • Demsar, J. (2006). Statistical comparisons of classifiers over multiple data sets. Journal of Machine Learning Research, 7(Jan), 1-30. (Pubitemid 43022939)
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 1-30
    • Demsar, J.1
  • 15
    • 0004708854 scopus 로고    scopus 로고
    • Exploiting the cost (in)sensitivity of decision tree splitting criteria
    • San Francisco, CA, USA. San Mateo: Morgan Kaufmann
    • Drummond, C., & Holte, R. C. (2000). Exploiting the cost (in)sensitivity of decision tree splitting criteria. In Proceedings of the 17th international conference on machine learning (ICML-2000), San Francisco, CA, USA (pp. 239-246). San Mateo: Morgan Kaufmann.
    • (2000) Proceedings of the 17th International Conference on Machine Learning (ICML-2000) , pp. 239-246
    • Drummond, C.1    Holte, R.C.2
  • 22
    • 0036680338 scopus 로고    scopus 로고
    • Learning cost-sensitive active classifiers
    • DOI 10.1016/S0004-3702(02)00209-6, PII S0004370202002096
    • Greiner, R., Grove, A. J., & Roth, D. (2002). Learning cost-sensitive active classifiers. Artificial Intelligence, 139(2), 137-174. (Pubitemid 34802160)
    • (2002) Artificial Intelligence , vol.139 , Issue.2 , pp. 137-174
    • Greiner, R.1    Grove, A.J.2    Roth, D.3
  • 27
    • 0034922742 scopus 로고    scopus 로고
    • Machine learning for medical diagnosis: History, state of the art and perspective
    • DOI 10.1016/S0933-3657(01)00077-X, PII S093336570100077X
    • Kononenko, I. (2001). Machine learning for medical diagnosis: history, state of the art and perspective. Artificial Intelligence in Medicine, 23(1), 89-109. (Pubitemid 32677979)
    • (2001) Artificial Intelligence in Medicine , vol.23 , Issue.1 , pp. 89-109
    • Kononenko, I.1
  • 30
    • 1242352526 scopus 로고    scopus 로고
    • Selective sampling for nearest neighbor classifiers
    • Lindenbaum, M., Markovitch, S., & Rusakov, D. (2004). Selective sampling for nearest neighbor classifiers. Machine Learning, 54(2), 125-152.
    • (2004) Machine Learning , vol.54 , Issue.2 , pp. 125-152
    • Lindenbaum, M.1    Markovitch, S.2    Rusakov, D.3
  • 36
    • 36849072609 scopus 로고    scopus 로고
    • Mining optimal decision trees from itemset lattices
    • DOI 10.1145/1281192.1281250, KDD-2007: Proceedings of the Thirteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
    • Nijssen, S., & Fromont, E. (2007). Mining optimal decision trees from itemset lattices. In Proceedings of the 13th ACM SIGKDD international conference on knowledge discovery and data mining (KDD-2007), San Jose, CA, USA (pp. 530-539). (Pubitemid 350229238)
    • (2007) Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , pp. 530-539
    • Nijssen, S.1    Fromont, E.2
  • 38
    • 0026154832 scopus 로고
    • Use of background knowledge in decision tree induction
    • DOI 10.1023/A:1022609710832
    • Nunez, M. (1991). The use of background knowledge in decision tree induction. Machine Learning, 6(3), 231-250. (Pubitemid 21737707)
    • (1991) Machine Learning , vol.6 , Issue.3 , pp. 231-250
    • Nunez Marlon1
  • 42
    • 0001834468 scopus 로고
    • Inductive policy: The pragmatics of bias selection
    • Provost, F., & Buchanan, B. (1995). Inductive policy: The pragmatics of bias selection. Machine Learning, 20(1-2), 35-61.
    • (1995) Machine Learning , vol.20 , Issue.1-2 , pp. 35-61
    • Provost, F.1    Buchanan, B.2
  • 43
    • 36849030268 scopus 로고    scopus 로고
    • Data acquisition and cost-effective predictive modeling: Targeting offers for electronic commerce
    • DOI 10.1145/1282100.1282172, ICEC 2007: Proceedings of the Ninth International Conference on Electronic Commerce
    • Provost, F., Melville, P., & Saar-Tsechansky, M. (2007). Data acquisition and cost-effective predictive modeling: targeting offers for electronic commerce. In Proceedings of the 9th international conference on electronic commerce (ICEC-2007) (pp. 389-398). (Pubitemid 350229452)
    • (2007) ACM International Conference Proceeding Series , vol.258 , pp. 389-398
    • Provost, F.1    Melville, P.2    Saar-Tsechansky, M.3
  • 45
    • 0030122886 scopus 로고    scopus 로고
    • Optimal composition of real-time systems
    • Russell, S. J., & Zilberstein, S. (1996). Optimal composition of real-time systems. Artificial Intelligence, 82(1-2), 181-213. (Pubitemid 126374152)
    • (1996) Artificial Intelligence , vol.82 , Issue.1-2 , pp. 181-213
    • Zilberstein, S.1    Russell, S.2
  • 46
    • 36849044683 scopus 로고    scopus 로고
    • Partial example acquisition in cost-sensitive learning
    • DOI 10.1145/1281192.1281261, KDD-2007: Proceedings of the Thirteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
    • Sheng, V. S., & Ling, C. X. (2007a). Partial example acquisition in cost-sensitive learning. In Proceedings of the 13th ACM SIGKDD international conference on knowledge discovery and data mining (KDD-2007), San Jose, CA, USA (pp. 638-646). (Pubitemid 350229249)
    • (2007) Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , pp. 638-646
    • Sheng, V.S.1    Ling, C.X.2
  • 48
    • 33750720941 scopus 로고    scopus 로고
    • Cost-sensitive test strategies
    • Proceedings of the 21st National Conference on Artificial Intelligence and the 18th Innovative Applications of Artificial Intelligence Conference, AAAI-06/IAAI-06
    • Sheng, S., Ling, C. X., Ni, A., & Zhang, S. (2006). Cost-sensitive test strategies. In Proceedings of the 21st national conference on artificial intelligence (AAAI-2006), Boston, MA, USA (pp. 482-487). (Pubitemid 44705330)
    • (2006) Proceedings of the National Conference on Artificial Intelligence , vol.1 , pp. 482-487
    • Sheng, V.S.1    Ling, C.X.2    Ni, A.3    Zhang, S.4
  • 51
    • 0000865580 scopus 로고
    • Cost-sensitive classification: Empirical evaluation of a hybrid genetic decision tree induction algorithm
    • Turney, P. D. (1995). Cost-sensitive classification: Empirical evaluation of a hybrid genetic decision tree induction algorith M. Journal of Artificial Intelligence Research, 2, 369-409.
    • (1995) Journal of Artificial Intelligence Research , vol.2 , pp. 369-409
    • Turney, P.D.1
  • 54
    • 33745217503 scopus 로고    scopus 로고
    • Technical Report 03-05-2005). School of Computing, Science and Engineering, University of Salford
    • Vadera, S. (2005). Inducing cost-sensitive non-linear decision trees (Technical Report 03-05-2005). School of Computing, Science and Engineering, University of Salford.
    • (2005) Inducing Cost-sensitive Non-linear Decision Trees
    • Vadera, S.1
  • 56
    • 77954410323 scopus 로고    scopus 로고
    • Supervised learning real-time traffic classifiers
    • Wang, Y., & Yu, S.-Z. (2009). Supervised learning real-time traffic classifiers. Journal of Networks, 4(7), 622-629.
    • (2009) Journal of Networks , vol.4 , Issue.7 , pp. 622-629
    • Wang, Y.1    Yu, S.-Z.2
  • 57
    • 84957865542 scopus 로고    scopus 로고
    • Cost-Sensitive Specialization
    • PRICAI'96: Topics in Artificial Intelligence
    • Webb, G. (1996). Cost-sensitive specialization. In Proceedings of the 4th pacific rim international conference on artificial intelligence (PRICAI-1996), London, UK (pp. 23-34). Berlin: Springer. (Pubitemid 126107988)
    • (1996) Lecture Notes in Computer Science , Issue.1114 , pp. 23-34
    • Webb, G.I.1
  • 58
    • 35148836033 scopus 로고    scopus 로고
    • Classifying under computational resource constraints: Anytime classification using probabilistic estimators
    • DOI 10.1007/s10994-007-5020-z
    • Yang, Y., Webb, G., Korb, K., & Ting, K. (2007). Classifying under computational resource constraints: anytime classification using probabilistic estimators. Machine Learning, 69(1), 35-53. (Pubitemid 47536396)
    • (2007) Machine Learning , vol.69 , Issue.1 , pp. 35-53
    • Yang, Y.1    Webb, G.2    Korb, K.3    Ting, K.M.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.