The coarse selection stage reduces greatly the size of the classifier pool using a clustering algorithm. The fine selection finds the near-optimal ensemble ...
The coarse selection stage reduces greatly the size of the classifier pool using a clustering algorithm. The fine selection finds the near-optimal ensemble ...
A good classifier ensemble should show high complementarity among classifiers to produce a high recognition rate and it should also have a small size to be ...
Authors: Young Won Kim, Il Seok Oh · Issue Date: 2009-09 · Citation: International Journal of Pattern Recognition and Artificial Intelligence, v.23, no.6, pp.1083 ...
Sep 15, 2007 · 거친 선택 단계에서는 분류기 풀의 크기를 적절하게 줄이는 것이 목적이다. 분류기 군집화 알고리즘을 사용하여 다양성을 최소로 희생하는 조건하에 ...
An ensemble feature selection method based on cluster grouping is proposed in this paper. Classification-related features are chosen using a ranking aggregation ...
Missing: Coarse- Fine
The coarse selection stage reduces greatly the size of the classifier pool using a clustering algorithm. The fine selection finds the near-optimal ensemble ...
This paper proposes a novel algorithm for multiple classifiers combination based on clustering and selection technique (called M3CS)
Missing: Fine | Show results with:Fine
Dec 28, 2010 · Abstract In this paper, we propose a classifier ensemble technique based on genetic algorithm (GA) for named entity recognition (NER).
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Coarse-to-Fine Classifier Ensemble Selection Using Clustering and Genetic Algorithms · Young-Won KimIl-Seok Oh. Computer Science. Int. J. Pattern Recognit ...