Algorithm for Visualization of Classification Results of Two-Category Data

A new algorithm called support vector visualization(SVV) was proposed for visualization of classification results of two-category data to meet the need in some applications.The SVV algorithm is based on support vector machine(SVM) and self-organizing mapping(SOM).The result of SVV is a 2D map to visualize highdimensional data,the boundary of the two-category data,as well as the distance between a datum and the boundary.Compared with SOM and Sammon mapping algorithms,experimental results on two datasets with different separability verify the feasibility and effectiveness of the SVV algorithm.