On Using Rule Induction in Multiple Classifiers with a Combiner Aggregation Strategy

Authors:
Jerzy Stefanowski;Slawomir Nowaczyk
Affiliations:
Poznan University of Technology, Poland;Lund University, Sweden
Venue:
ISDA '05 Proceedings of the 5th International Conference on Intelligent Systems Design and Applications
Year:
2005

Citing 0
Cited 3

Feature Selection Algorithm for Multiple Classifier Systems: A Hybrid Approach

Fundamenta Informaticae - Concurrency Specification and Programming (CS&P)
On combined classifiers, rule induction and rough sets

Transactions on rough sets VI
Feature Selection Algorithm for Multiple Classifier Systems: A Hybrid Approach

Fundamenta Informaticae - Concurrency Specification and Programming (CS&P)

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Abstract

The paper is an experimental study of using the rough sets based rule induction algorithmMODLEM in the framework of multiple classifiers. Particular attention is paid to using a meta-classifier called combiner, which learns how to aggregate answers of component classifiers. The experimental results confirm that the range of classification improvement for the combiner depends on the independence of errors made by the component classifiers. Moreover, we summarize the experience with using MODLEM in other multiple classifiers, namely the bagging and n2 classifiers.