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This paper proposes a rule-plus-exemplar classification system to deal with the concept growth problem. Unlike concept drift, the concept is expanding with time rather than becoming obsolete. The proposed system is able to grow and evolve to incrementally learn the concept. It also adapts to the change to provide reliable classification even when the sample is unfamiliar with respect to the available...
Scene classification is useful for automatic organization of personal digital photographs or visual guidance of robots, but it is a time consuming and labor-intensive task to label adequate examples to train robust classifiers. Active learning is a key technique to reduce human-labeling burden by exploring an optimal subset from unlabeled data. In this paper we use a batch mode incremental and active...
The paper summarizes the characteristics of the support vector set and its changes in the incremental learning process, analyzes the concept of the support vector classification and the relationship with the separate super plane, gives the improvement of the Syedpsilas method, and verifies the superiority of the algorithm through numerical experimentation.
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