Ensemble of Classifiers Based on Hard Instances

机译：基于硬实例的分类器集合

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There are several classification problems, which are difficult to solve using a single classifier because of the complexity of the decision boundary. Whereas, a wide variety of multiple classifier systems have been built with the purpose of improving the recognition process. There is no universal method performing the best. The aim of this paper is to show another model of combining classifiers. This model is based on the use of different classifier models. It makes clusters to divide the dataset, taking into account the performance of the base classifiers. The system learns how to decide from the groups, by a meta-classifier, who are the best classifiers for a given pattern. In order to compare the new model with well-known classifier ensembles, we carried out experiments with some international databases. The results demonstrate that this new model can achieve similar or better performance than the classic ensembles.

机译：存在多个分类问题，由于决策边界的复杂性，使用单个分类器很难解决这些问题。鉴于，已经建立了各种各样的多种分类器系统，以改善识别过程。没有通用方法可以发挥最佳效果。本文的目的是展示另一个组合分类器的模型。该模型基于不同分类器模型的使用。考虑到基本分类器的性能，它使聚类划分数据集。系统将学习如何通过元分类器从组中确定对于给定模式而言最佳的分类器。为了将新模型与著名的分类器集合进行比较，我们对一些国际数据库进行了实验。结果表明，与经典合奏相比，该新模型可以实现相似或更好的性能。

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来源
《Pattern recognition》|2011年|p.67-74|共8页
会议地点 Cancun(MX);Cancun(MX)
作者
Isis Bonet; Abdel Rodriguez; Ricardo Grau; Maria M. Garcia;
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作者单位

Center of Studies on Informatics, Central University of Las Villas, Santa Clara, Cuba;

Center of Studies on Informatics, Central University of Las Villas, Santa Clara, Cuba;

Center of Studies on Informatics, Central University of Las Villas, Santa Clara, Cuba;

Center of Studies on Informatics, Central University of Las Villas, Santa Clara, Cuba;

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原文格式 PDF
正文语种 eng
中图分类模式识别与装置;
关键词
multiple classifiers; ensemble classifiers; classification; pattern recognition;

机译：多个分类器；集成分类器；分类;模式识别;

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4. Ensemble of Classifiers Based on Hard Instances [C] . Isis Bonet, Abdel Rodriguez, Ricardo Grau, Mexican Conference on Pattern Recognition . 2011

机译：基于硬实例的分类器集合
5. Instance selection for model-based classifiers [D] . Bennette, Walter Dean. 2014

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6. Localized instance fusion of MRI data of Alzheimer’s disease for classification based on instance transfer ensemble learning [O] . Xiaoheng Tan, Yuchuan Liu, Yongming Li, 2018

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7. Ensemble of Classifiers Based on Hard Instances [O] . Isis Bonet, Abdel Rodríguez, Ricardo Grau, 2011

机译：基于硬实例的分类器集合

Ensemble of Classifiers Based on Hard Instances

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