摘要集成学习因其能显著提高一个学习系统的泛化能力而得到了机器学习界的广泛关注,
但随着基学习机数目的增多, 集成学习机的预测速度明显下降, 其所需的存储空间也迅速增加 …

In this article, we present a semisupervised support vector machine that uses self-training
approach. We then construct an ensemble of semisupervised SVM classifiers to address the …

In this paper we present a novel approach for combining GP-based ensembles by means of
a Bayesian Network. The proposed system is able to effectively learn decision tree …

Handwritten recognition is a very active research domain that led to several works in the
literature for the Latin Writing. The current systems tendency is oriented toward the …

In constructing a classifier ensemble diversity is more important as the accuracy of its
elements. To reach a diverse ensemble, one approach is to produce a pool of classifiers …

Owing to the strict relationship between protein structure and function, the prediction of
protein tertiary structure has become one of the most important tasks in recent years. Despite …

The International Conference on Information and Communication Systems (ICICS 2011) -
Cogprints Logo Cogprints Home About Browse by Year Browse by Subject The …

Multiple classifier systems (MCS) have become a popular classification paradigm for strong
generalization performance. Diversity measures play an important role in constructing and …

Ensemble methods are statistical and computational learning procedures reminiscent of the
human social learning behaviour of seeking several opinions before making any crucial …