Concurrent engineering draws together team working and cooperation, with the aim of
reducing the need for costly design modifications in the later stages of design and product …

We present a method to learn maximal generalized decision rules from databases by
integrating discretization, generalization and rough set feature selection. Our method …

We present a data mining method which integrates discretization, generalization and rough
set feature selection. Our method reduces the data horizontally and vertically. In the first …

基于粗糙集理论的多传感器信息融合-[维普官方网站]-www.cqvip.com-维普网  我的维普 购物车
充值 客服 首页 | 期刊大全 | 文献分类 | 优先出版 | 论文检测 | 论文选题 | 在线分享 | 会议平台 | 学术 …

This dissertation presents methods for increasing the accuracy of probabilistic classification
rules learned from noisy, relational data. It addresses the problem of learning probabilistic …

Learning of rules can be stated as an optimization problem. While current learning
algorithms use variants of hill climbing and beam search for combinatorial optimization …

The idea of learning of multiple knowledge is to generate several theories instead of one
theory for the classification of new objects, hoping that combining of answers of more …

In the first part of the paper we describe how different agents can arrive at different (but
overlapping) views of reality. Although the agents can cooperate when answering queries, it …

In sparse data environments, greater classification accuracy can be achieved by learning
several concept descriptions of the data and combining their classifications. Stochastic …

This paper introduces a new ensemble technique, cluster-based concurrent decomposition
(CBCD) that induces an ensemble of classifiers by decomposing the training set into …