The traditional classification system often chooses the Naive Bayesian algorithm as the classification algorithm. In the course of the study, we find that the Naive Bayesian model(NBC) has the following conditions:all the characteristics do not mutually influence each other, and the feature attribute weights is 1. But we find that is not the case after a study. In the classification of data, some features may have a greater impact on the classification results, while some may have little impact. In order to optimize the algorithm, we need to attach different weights to different features, so as to obtain the classification results more objectively. This paper studies two kinds of calculation methods of attributing weight based on the traditional algorithm. At the same time, considering the characteristics of mobile phone forensic data, it proposes the calculation method of two kinds of improved weight suitable for mobile phone forensic data. This paper researches the improvement principle of research, compares the improved calculation method of weight with the traditional calculation method in their impacts on the classification results using the same classification algorithm with the same data.