An efficient document classification algorithm based on kernel LDE

To efficiently deal with document classification problem, an efficient document classification algorithm based on kernel local discriminant embedding (kernel LDE) is proposed in this paper. The high-dimensional document data are first mapped into lower-dimensional feature space, then the SVM classifier is applied to classify documents. The experimental results demonstrate that the proposed algorithm achieves much better performance than other traditional document classification algorithms.