In view of the discovery that the different network data features have different influence on classification results in SVM-based network intrusion detection,a new SVM weighted feature classification method is brought forward in order to get optimal classification plane.

Based on the fundamental theory of clustering analysis and fuzzy mathematics,the numerical and attributes characteristic samples of history flood were established,and the characteristic samples were analyzed on a basin by using feature weighted fuzzy clustering algorithm.

Feature weighted is the general case of feature selection,which has better performance than(or at least has the same performance as) feature selection.

In this paper,distance metric and feature weighted algorithms have been provided for pretreatment of data which are gathered in the network.

Analysis and improvement of feature weighting method TF·IDF in text categorization;

To weaken the effects of blur edges and much noise in infrared images,a novel approach on recognition for infrared images based on Gabor filters and feature weighting is presented in this paper.

In this paper we focus our attention on the works in this field, which include four parts: an improved Gabor feature extraction algorithm based on feature weighting, infrared vehicle detection with Gabor filters and Support Vector Machines (SVM), vehicle clas.

Mixed fuzzy clustering analysis based on feature weights and its application in classification of flood disaster grade

Study several common recognition algorithms,then advance a full-area feature weight template matching algorithm.

In the Fuzzy c-Means algorithm, considering the particular contributions of different feature, a feature weight fuzzy clustering algorithm is introduced in this paper.