Titlebook: Intelligent Data Engineering and Automated Learning – IDEAL 2015; 16th International C Konrad Jackowski,Robert Burduk,Hujun Yin Conference

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书目名称Intelligent Data Engineering and Automated Learning – IDEAL 2015影响因子(影响力)




书目名称Intelligent Data Engineering and Automated Learning – IDEAL 2015影响因子(影响力)学科排名




书目名称Intelligent Data Engineering and Automated Learning – IDEAL 2015网络公开度




书目名称Intelligent Data Engineering and Automated Learning – IDEAL 2015网络公开度学科排名




书目名称Intelligent Data Engineering and Automated Learning – IDEAL 2015被引频次




书目名称Intelligent Data Engineering and Automated Learning – IDEAL 2015被引频次学科排名




书目名称Intelligent Data Engineering and Automated Learning – IDEAL 2015年度引用




书目名称Intelligent Data Engineering and Automated Learning – IDEAL 2015年度引用学科排名




书目名称Intelligent Data Engineering and Automated Learning – IDEAL 2015读者反馈




书目名称Intelligent Data Engineering and Automated Learning – IDEAL 2015读者反馈学科排名

flamboyant

Web Genre Classification via Hierarchical Multi-label Classification, of the result web pages. This opens the need for web genre prediction based on the information on the web page. Typically, this task is addressed as multi-class classification, with some recent studies advocating the use of multi-label classification. In this paper, we propose to exploit the web ge

小步舞

Multi-agent Reinforcement Learning for Control Systems: Challenges and Proposals,. We review the most important MARL algorithms from a control perspective focusing on on-line and model-free methods. We review some of sophisticated developments in the state-of-the-art of single-agent Reinforcement Learning which may be transferred to MARL, listing the most important remaining cha

小隔间

Optimal Filtering for Time Series Classification,asures, however, seems to completely ignore the possibility of applying a filter first. In this paper, we investigate to what extent the benefit obtained by more complex distance measures may be achieved by simply applying a filter to the original series (while sticking to Euclidean distance). We pr

Instinctive

与野兽博斗者

音乐等

Managing Monotonicity in Classification by a Pruned Random Forest,do not guarantee to produce model that satisfy the monotonicity constraints. Some algorithms have been developed to manage this issue, such as decision trees which have modified the growing and pruning mechanisms. In this contribution we study the suitability of using these mechanisms in the generat

悬挂

多节

An Extension of Multi-label Binary Relevance Models Based on Randomized Reference Classifier and Lofication. We proposed a novel solution to the problem of correcting Binary Relevance ensembles. The main step of the correction procedure is to compute label-wise competence and cross-competence measures, which model error pattern of the underlying classifier. The method was evaluated using 20 bench

充足

Fusion of Self-Organizing Maps with Different Sizes,esults of each network. This work presents a methodology to aggregate the results of several Kohonen Self-Organizing Maps in an ensemble. Computational simulations demonstrate an increase in the accuracy classification and the proposed method effectiveness was evidenced by the Wilcoxon Signed Rank T