Knowledge Discovery Through Induction with Randomization Testing (1991)

Cached

Download Links

by David Jensen
Citations:15 - 3 self

Documents Related by Co-Citation

60 On the connection between in-sample testing and generalization error. Complex Systems 6:47–94 – D H Wolpert - 1992
8 Statistical significance in inductive learning – Olivier Gascuel, Gilles Caraux - 1992
3331 Induction of Decision Trees – J. R. Quinlan - 1986
3866 Classification of Regression Trees – L Breiman, J Friedman, R Olshen, C Stone - 1984
66 The Effects of Training Set Size on Decision Tree Complexity – Oates - 1997
144 A conservation law for generalization performance – C Schaffer - 1994
13 Which method learns most from the data – A Feelders, W Verkooijen - 1995
3 Labeling space: A tool for thinking about significance testing in knowledge discovery. Office of Technology Assessment – David Jensen - 1995
5 Statistical thinking for behavioral scientists – D K Hildebrand - 1986
7 Statistical tests for comparing supervised learning algorithms (Technical Report – T Dietterich - 1996
35 Statistical Evaluation of Neural Network Experiments: Minimum Requirements and Current Practice – Arthur Flexer - 1994
18 Data Mining as an Industry – Frank T Denton - 1985
51 A Study of Experimental Evaluations of Neural Network Learning Algorithms: Current Research Practice – Lutz Prechelt, Fakultat Fur Informatik - 1994
99 Symbolic and neural learning algorithms: an experimental comparison – Jude W. Shavlik, Raymond J. Mooney, Geoffrey G. Towell - 1991
133 Experimental Designs – W Cochran, G Cox - 1957
434 Very simple classification rules perform well on most commonly used datasets – Robert C. Holte - 1993
737 UCI repository of machine learning databases – P Murphy - 1992
100 The Analysis of Contingency Tables – B S Everitt - 1992
42 Multi-interval discretization of continuous valued attributes for classification learning – U Fayyad, K Irani - 1993