On Improving Performance and Increasing Useability of EFS
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Dynamic rule split-and-merge strategies during incremental learning for an improved representation of local partitions in the feature space (Section 5.1).
An on-line feature weighting concept as a kind of on-line adaptive soft feature selection in evolving fuzzy systems, which helps to reduce the curse of dimensionality dynamically and in smooth manner in case of high-dimensional problems (Section 5.2).
Active and semi-supervised learning the reduce labelling and feedback effort of operators at on-line classification and identification systems (Section 5.3).
The concept of incremental classifier fusion for boosting performance of single evolving fuzzy classifiers by exploiting the diversity in their predictions (Section 5.4).
An introduction to the concept of dynamic data mining, where the data batches are not temporally but spatially distributed and loaded (Section 5.5.1).
Lazy learning with fuzzy systems: an alternative concept to evolving fuzzy systems (Section 5.5.2).
KeywordsFuzzy System Membership Degree Unlabelled Data Feature Weight Cluster Partition
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