Decision tree instability and active learning

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4701 LNAI, Issue , 2007, Pages 128-139

  Dwyer, Kenneth ^a   Holte, Robert ^a  

^a UNIVERSITY OF ALBERTA   (Canada)

Author keywords

Active learning; Decision tree learning; Ensemble methods; Evaluation of learning methods

Indexed keywords

DECISION TREES; KNOWLEDGE ACQUISITION; LEARNING SYSTEMS; MATHEMATICAL MODELS; QUERY PROCESSING;

ACTIVE LEARNING; DECISION TREE LEARNING; ENSEMBLE METHODS; EVALUATION OF LEARNING METHODS;

LEARNING ALGORITHMS;

EID: 38049132692     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-74958-5_15     Document Type: Conference Paper

References (17)

1. Breiman, L.: Bagging predictors. Machine Learning 24(2), 123-140 (1996)
2. Turney, P.D.: Bias and the quantification of stability. Machine Learning 20(1-2), 23-33 (1995)
3. Quinlan, J.R.: Improved use of continuous attributes in C4.5. JAIR 4, 77-90 (1996)
4. Dwyer, K.D.: Decision tree instability and active learning. Master's thesis, University of Alberta (2007)
5. Abe, N., Mamitsuka, H.: Query learning strategies using boosting and bagging. In: Proc. ICML '98, pp. 1-9 (1998)
6. Dietterich, T.G., Kearns, M., Mansour, Y.: Applying the weak learning framework to understand and improve C4.5. In: Proc. ICML '96, pp. 96-104 (1996)
7. Drummond, C., Holte, R.C.: Exploiting the cost (in)sensitivity of decision tree splitting criteria. In: Proc. ICML '00, pp. 239-246 (2000)
8. Alpaydin, E.: Introduction to Machine Learning. MIT Press, Cambridge (2004)
9. Newman, D.J., Hettich, S., Blake, C.L., Merz, C.J.: UCI ML Repository (1998)
10. Shannon, W.D., Banks, D.L.: Combining classification trees using MLE. Statistics in Medicine 18(6), 727-740 (1999)
11. Pérez, J.M., Muguerza, J., Arbelaitz, O., Gurrutxaga, I., Martín, J.I.: Consolidated trees: Classifiers with stable explanation. In: Singh, S., Singh, M., Apte, C., Perner, P. (eds.) ICAPR 2005. LNCS, vol. 3686, pp. 99-107. Springer, Heidelberg (2005)
12. Cohn, D.A., Atlas, L.E., Ladner, R.E.: Improving generalization with active learning. Machine Learning 15(2), 201-221 (1992)
13. Lewis, D.D., Catlett, J.: Heterogeneous uncertainty sampling for supervised learning. In: Proc. ICML '94, pp. 148-156 (1994)
14. Saar-Tsechansky, M., Provost, F.: Active sampling for class probability estimation and ranking. Machine Learning 54(2), 153-178 (2004)
15. Roy, N., McCallum, A.: Toward optimal active learning through sampling estimation of error reduction. In: Proc. ICML '01, pp. 441-448 (2001)
16. Demšar, J.: Statistical comparisons of classifiers over multiple data sets. JMLR 7, 1-30 (2006)
17. Domingos, P.M.: Knowledge acquisition from examples via multiple models. In: Proc. ICML '97, pp. 98-106 (1997)