A general decision layer text classification fusion model

摘要

An general decision layer text classification fusion model for higher precision, is proposed, which based on model theory of information fusion, and different classification algorithm of the feature layer fusion centre having different pre-processing, their classification results input into the decision layer fusion centre separately. And the final classification result output from decision layer fusion centre. KNN, SVM and BP Net are used in feature layer, and D-S Theory is used in decision layer. The model is realized in the experiment. From the experiment and contrast, the text classification fusion model can improve the classification precision effectively.