According to the phenomena that the calculation of prior probability in text classification is time-consuming and has little effect on the classification result，and the accuracy loss of posterior probability affects the accuracy of classification, the classical naive Bayes algorithm is improved and a new text classification algorithm is proposed which restrains the effect of prior probability and amplifies the effect of posterior probability. In the new algorithm, the calculation of prior probability is removed and an amplification factor is added to the calculation of posterior probability. The experiments prove that removing the calculation of prior probability in text classification can accelerate the classification speed and has little effect on the classification accuracy, and adding an amplification factor in the calculation of posterior probability can reduce the effect of error propagation and improve the classification accuracy.