Consolidated trees: Classifiers with stable explanation. A model to achieve the desired stability in explanation

Lecture Notes in Computer Science

Volumn 3686, Issue PART I, 2005, Pages 99-107

  Pérez, Jesús M ^a   Muguerza, Javier ^a   Arbelaitz, Olatz ^a   Gurrutxaga, Ibai ^a   Martín, José I ^a  

^a UNIVERSITY OF THE BASQUE COUNTRY UPV EHU   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); CONVERGENCE OF NUMERICAL METHODS; ERROR ANALYSIS; MATHEMATICAL MODELS; PROBLEM SOLVING; STATISTICAL METHODS; TREES (MATHEMATICS);

CLASSIFICATION TREES; CONSOLIDATED TREES CONSTRUCTION ALGORITHM (CTC); STRUCTURAL STABILITY; SUBSAMPLING TECHNIQUES;

LEARNING SYSTEMS;

EID: 27244443267     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/11551188_11     Document Type: Conference Paper

References (9)

1. Blake, C.L., Merz, C.J.: UCI Repository of Machine Learning Databases, University of California, Irvine, Dept. of Information and Computer Sciences. http://www.ics.uci.edu/~mlearn/MLRepository.html, (1998).
2. Dietterich T.G.: Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms, Neural Computation, Vol. 10, No. 7, (1998) 1895-1924.
3. Domingos P.: Knowledge acquisition from examples via multiple models. Proc. 14th International Conference on Machine Learning Nashville, TN (1997) 98-106.
4. Drummond C., Holte R.C.: Exploiting the Cost (In)sensitivity of Decision Tree Splitting Criteria, Proceedings of the 17th International Conference on Machine Learning, (2000) 239-246.
5. Hastie T., Tibshirani R. Friedman J.: The Elements of Statistical Learning. Springer-Verlang (es). ISBN: 0-387-95284-5, (2001).
6. Pérez J.M., Muguerza J., Arbelaitz O., Gurrutxaga I., Martin J.I.: Behavior of Consolidated Trees when using Resampling Techniques. Proceedings of the 4th International Workshop on Pattern Recognition in Information Systems (PRIS-2004), Porto, Portugal (2004), 139-148.
7. Pérez J.M., Muguerza J., Arbelaitz O., Gurrutxaga I., Martin J.I.: Analysis of structural convergence of Consolidated Trees when resampling is required. Proceedings of the 3rd Australasian Data Mining Conference (AusDM04), Cairns, Australia (2004), 9-21.
8. Quinlan J.R.: C4.5: Programs for Machine Learning, Morgan Kaufmann Publishers Inc.(eds), San Mateo, California, (1993).
9. Turney P. Bias and the quantification of stability. Machine Learning, 20 (1995), 23-33.