<![CDATA[Aiming at the phenomenon that in text classification the calculation of prior probability is time-consuming and has little effect on the classification results and the error propagation of posterior probability affects the accuracy of classification, this paper improves the classical naïve bayes algorithm and proposes a new text classification algorithm which accelerates the speed by removing the calculation of prior probability and reduces the accuracy loss of error propagation by adding an amplification factor .The experiments prove that removing the calculation of prior probability can accelerate the classification speed obviously 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. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.4180 ]]>
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