Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms (1998)

by Thomas G. Dietterich
Citations:416 - 8 self

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94 Wrappers For Performance Enhancement And Oblivious Decision Graphs – Ron Kohavi, Yoav Shoham, Jerry Friedman - 1995
14 Improved Class Probability Estimates from Decision Tree Models – Dragos D. Margineantu, Thomas G. Dietterich - 2001
k. Results indicate that this procedure is very effective in estimating good feature weights (Table 4.8). Particularly the results obtained in the – Banded Sinusoidal Tasks - 1994
102 Machine-Learning Research -- Four Current Directions – Thomas G. Dietterich
29 Nearest neighbor classification from multiple feature subsets – Stephen D. Bay - 1999
122 Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey – Sreerama K. Murthy - 1997
449 An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants – Eric Bauer, Ron Kohavi - 1999
775 Wrappers for feature subset selection – Ron Kohavi , George H. John - 1997
115 Inference for the generalization error – Série Scientifique, École Des Hautes Études Commerciales, École Polytechnique, Université Concordia, Université De Montréal, Université Laval, Université Mcgill, Bell Québec, Claude Nadeau, Claude Nadeau, Yoshua Bengio, Yoshua Bengio - 2003
27 Classification and Regression using Mixtures of Experts – Steven Richard Waterhouse - 1997
11 A comprehensive case study: An examination of machine learning and connectionist algorithms – Frederick Zarndt - 1995
364 An experimental comparison of three methods for constructing ensembles of decision trees – Thomas G. Dietterich, Doug Fisher - 2000
131 Error-Correcting Output Coding Corrects Bias and Variance – Eun Bae Kong, Thomas G. Dietterich - 1995
39 Combining Nearest Neighbor Classifiers Through Multiple Feature Subsets – Stephen D. Bay
2 Effective Pruning of Neural Network Classifier Ensembles – Aleksandar Lazarevic, Ar Lazarevic, Zoran Obradovic
22 Prototype Selection for Composite Nearest Neighbor Classifiers – David B. Skalak - 1997
151 Popular ensemble methods: an empirical study – David Opitz, Richard Maclin - 1999
144 Bias plus variance decomposition for zero-one loss functions – Ron Kohavi - 1996
50 Tree induction vs. logistic regression: A learning-curve analysis – Claudia Perlich, Foster Provost, Jeffrey S. Simonoff - 2001