DOI: 10.3724/SP.J.1146.2012.01707

Journal of Electronics & Information Technology (电子与信息学报) 2013/35:12 PP.2896-2900

An Improved Rotation Forest Classification Algorithm

With the development of information technology, people tend to deal with large amount of data with complex data types. Therefore, how to deal with these data well to achieve good classification results is a highly challenging task. In this paper, a new hybrid algorithm ROF-ELM is proposed, which both combines the advantages of ROtation Forest (ROF) algorithm and Extreme Learning Machine (ELM) neural network. The new algorithm solves the over-fitting problem of the original Rotation Forest algorithm and improves the classification accuracy as well. The proposed ROF-ELM algorithm is experimented on the UCI data sets and remote sensing image. Compared to classical ensemble algorithm, ROF-ELM improves the classification accuracy, and has high stability and generalization performance at the same time.

Key words:Feature extraction,ROtation Forest (ROF),Extreme Learning Machine (ELM),Ensemble classifier

ReleaseDate:2014-07-21 17:04:33