Combining Classifiers Using Correspondence Analysis (1998)

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by Christopher Merz
Citations:4 - 0 self

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51 Using Correspondence Analysis to Combine Classifiers – Christopher J. Merz, Sal Stolfo - 1998
181 Popular ensemble methods: an empirical study – David Opitz, Richard Maclin - 1999
28 A Principal Components Approach to Combining Regression Estimates – Christopher J. Merz, MICHAEL J. PAZZANI, Sal Stolfo - 1998
13 Cost Complexity-based Pruning of Ensemble Classifiers – Andreas L. Prodromidis, Salvatore J. Stolfo - 1999
44 An Extensible Meta-Learning Approach for Scalable and Accurate Inductive Learning – Philip Kin-Wah Chan - 1996
4 Effective and Efficient Pruning of Meta-Classifiers in a Distributed Data Mining System – Andreas L. Prodromidis, Salvatore J. Stolfo, Philip K. Chan - 1999
16 Robust Combining of Disparate Classifiers through Order Statistics – Kagan Tumer, Joydeep Ghosh - 2001
80 Meta-Learning in Distributed Data Mining Systems: Issues and Approaches – Andreas L. Prodromidis, Philip K. Chan, Salvatore J. Stolfo - 2000
5 Performance and efficiency: Recent advances in supervised learning – Sheng Ma, Chuanyi Ji - 1999
67 Ensembling Neural Networks: Many Could Be Better Than All – Zhi-hua Zhou, Jianxin Wu, Wei Tang - 2002
79 Issues in Stacked Generalization – Kai Ming Ting, Ian H. Witten - 1999
26 Prototype Selection for Composite Nearest Neighbor Classifiers – David B. Skalak - 1997
114 Machine-Learning Research -- Four Current Directions – Thomas G. Dietterich
29 Knowledge Discovery Via Multiple Models – Pedro Domingos - 1998
10 Classifier Ensembles: Select Real-World Applications – Nikunj C. Oza, Kagan Tumer - 2008
65 Linear and Order Statistics Combiners for Pattern Classification – Kagan Tumer, Joydeep Ghosh - 1999
3 RotBoost: a technique for combining rotation forest and AdaBoost – Chun-xia Zhang, Jiang-she Zhang - 2008
22 Dynamical Selection of Learning Algorithms – Christopher Merz - 1995
25 Cloud Classification Using Error-Correcting Output Codes – David W. Aha, Richard L. Bankert - 1996