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Simplifying Decision Trees (1986)

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by J. R. Quinlan
Citations:2888 - 3 self
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BibTeX

@MISC{Quinlan86simplifyingdecision,
    author = {J. R. Quinlan},
    title = {Simplifying Decision Trees},
    year = {1986}
}

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Abstract

Many systems have been developed for constructing decision trees from collections of examples. Although the decision trees generated by these methods are accurate and efficient, they often suffer the disadvantage of excessive complexity that can render them incomprehensible to experts. It is questionable whether opaque structures of this kind can be described as knowledge, no matter how well they function. This paper dis- cusses techniques for simplifying decision trees without compromising their accuracy. Four methods are described, illustrated, and compared on a test-bed of decision trees from a variety of domains.

Citations

5666 Probabilistic reasoning in intelligent systems - Pearl - 1988
4071 C4.5: Programs for machine learning - Quinlan - 1993
3143 Classification and Regression Trees - Breiman, Friedman, et al. - 1984
1998 Bagging predictors - Breiman - 1996
1714 Schapire R: A decision-theoretic generalization of online learning and an application to boosting - Freund - 1997
1325 Experiments with a new boosting algorithm - Freund, Schapire - 1996
897 Instance-Based Learning Algorithms - Aha, Kibler, et al. - 1991
606 W: Boosting the Margin: A New Explanation for the Effectiveness of Voting Methods. The Annals of Statistics - Schapire, Freund, et al. - 1998
556 The weighted majority algorithm - Littlestone, Warmuth - 1994
545 Some Studies in Machine Learning using the Game of Checkers - Samuel - 2000
449 Kohavi R: An empirical comparison of voting classification algorithms - Bauer - 1999
347 Learning decision lists - Rivest - 1987
292 Learning Efficient Classification Procedures and their Application to Chess End Games - Quinlan - 1983
253 Beyond independence: conditions for the optimality of the simple bayesian classifier - Domingos, Pazzani - 1996
251 Bagging, boosting, and C4.5 - Quinlan - 1996
232 R.E.: Learning from observation: Conceptual clustering - Michalski, Stepp - 1984
153 Improved Use of Continuous Attributes in C4.5 - Quinlan - 1996
127 A Guide to Expert Systems - Waterman - 1986
127 Learning Machines - Nilsson
123 Introduction to Mathematical Statistics - Hogg, Allen, et al. - 2004
96 Experiments in induction - Hunt, Marin - 1966
96 The effect of noise on concept learning - Quinlan - 1985
91 variance and arcing classifiers - Breiman, “Bias - 1996
89 Pattern Recognition a Rule-Guided Inductive Inference - Michalski - 1980
88 Discovering rules by induction from large collections of examples - Quinlan - 1979
55 Model-directed learning of production rules - Buchanan, Mitchell - 1978
53 Eds.): Machine Learning: An - Michalski, Carbonell, et al. - 1986
53 Rediscovering chemistry with the Bacon system - Langley, Bradshaw, et al. - 1983
51 Further experimental evidence against the utility of Occam’s Razor - Webb
50 Structured Induction in Expert Systems - Shapiro - 1987
48 Inductive knowledge acquisition: A case study - Quinlan, Compton, et al. - 1987
34 An inference technique for integrating knowledge from disparate sources - Garvey, Lowrance, et al. - 1981
28 Experiments in automatic learning of medical diagnostic rules - Konenko, Bratko - 1994
27 On the connection between the complexity and credibility of inferred models - Pearl - 1978
21 Decision Trees and Multi-values Attributes - Quinlan - 1998
15 Experience in the use of an inductive system in knowledge engineering - Hart - 1985
12 Semi-autonomous acquisition of pattern-based knowledge - Quinlan - 1982
9 Current developments in expert systems - Michie - 1987
9 Artificial Intelligence, 2nd Edition - Winston - 1984
7 Concept learning: An information processing problem - Hunt - 1962
7 Learning from noisy data - Quinlan - 1986
5 Expert systems in the 1980s - Feigenbaum - 1981
3 Concept formation from very large training sets - O'Keefe - 1983
3 Concept development for expert system knowledge bases - Sammut - 1985
3 An appraisal of a decision-tree approach to image classification - Shepherd - 1983
2 Tables for Testing Significance in a 2 x 2 Contingency Table - Finney, Latscha, et al. - 1963
2 Experiments on the mechanisation of game-learning 2 - Rule-based learning and the human window - Michie - 1982
2 ACLS user manual - Patterson, Niblett - 1983
1 An experimental comparison of two learning programs in three medical domains - Lavra, Mozeti, et al. - 1986
1 Learning by being told and learning by examples: an experimental comparison of the two methods of knowledge acquisition in the context of developing an expert system for soybean disease diagnosis - Michalski, Chilausky - 1980
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