Active Bibliography

4 On the Development of Inductive Learning Algorithms: Generating Flexible and Adaptable Concept Representations – Ricardo Vilalta - 1998
39 Local Cascade Generalization – João Gama - 1998
1 Integrating Boosting and Stochastic Attribute Selection Committees for Further Improving the Performance of Decision Tree Learning – Zijian Zheng, Geoffrey I. Webb, Kai Ming Ting - 1998
69 Extracting Comprehensible Models from Trained Neural Networks – W. Craven - 1996
1 Paradigms for Machine Learning – Jeffrey C. Schlimmer, Pat Langley - 1991
Cost-Sensitive Decision Tree Learning . . . – Susan Elaine Lomax - 2013
18 Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees – Zijian Zheng , Geoffrey I. Webb, Kai Ming Ting - 1999
39 Online ensemble learning – Nikunj Chandrakant Oza - 2001
2 Knowledge Discovery From Distributed And Textual Data – Vincent Wing-sing Cho - 1999
13 Pruning decision trees and lists – Eibe Frank - 2000
44 An Extensible Meta-Learning Approach for Scalable and Accurate Inductive Learning – Philip Kin-Wah Chan - 1996
15 Boosting Methods for Regression – Nigel Duffy, David Helmbold - 200
c ○ 2002 Kluwer Academic Publishers. Manufactured in The Netherlands. Boosting Methods for Regression ∗ – Nigel Duffy, David Helmbold, Jyrki Kivinen
3 Classifying Unseen Cases with Many Missing Values – Zijian Zheng, Boon Toh Low - 1999
15 Stochastic attribute selection committees – Zijian Zheng, Geoffrey I. Webb - 1998
2 Creating Diverse Ensemble Classifiers – Prem Melville, Supervisor Raymond, J. Mooney - 2003
26 Prototype Selection for Composite Nearest Neighbor Classifiers – David B. Skalak - 1997
110 An introduction to boosting and leveraging – Ron Meir, Gunnar Rätsch - 2003
9 A case study of applying boosting Naive Bayes to claim fraud diagnosis – Stijn Viaene, Richard A. Derrig, Guido Dedene - 2004