%0 Journal Article
%T Study of Web document classification based on best weight neural network ensembles<br>基于最优权重的神经网络集成文本分类研究
%A ZHOU Pu-xiong
%A <br>周朴雄
%J 计算机应用研究
%D 2008
%I 
%X Inspired by the ideas of neural network ensembles, this paper constructed a multi-BP neural network modeling with best weights that was based the strategy of minimum estimate error. To do this, according to the capability of classification of each network and the degree of each network related to other networks, the different weight would assign to the probability esti-mates of maximuma posterior ( MAP) . Further, improved the accuracy of estimate and classification. The experimental results of English database demonstrate that this model hold the better accuracy and speed than the Bayes and kNN models.
%K document classification
%K neural network ensembles
%K accuracy<br>文本分类
%K 神经网络集成
%K 精度
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=8A13C487C7FC4966422D664B9BAD6B90&yid=67289AFF6305E306&vid=C5154311167311FE&iid=F3090AE9B60B7ED1&sid=5371E3AD73F1A656&eid=FB7E7E2CE880728A&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=8