Matrix projection algorithm for text classification

A new algorithm,namely matrix projection algorithmi,s proposed for text classification to solve the key problems of reducing dimension of features and improving efficiency and accuracy.It is based on matrix operation,which projects three-dimensional feature space of training samples onto two-dimensional feature space and obtains a normalized feature vec-tor,achieves the aims of reduction in feature dimensions and accurate computation of feature term weights.Comparing with several typical algorithmst,he proposed algorithm is remarkably superior to them in terms of accuracy and time,and the F1 value reaches 92.29% and 96.03% respectively on two typical data sets.