Abstract
With the help of Police Performance Appraisal System, the working quality of the Public Security Organs of Tianjin has been improved. As a part of the system, Police Performance Appraisal Early Warning can accelerate feedback speed and improve the efficiency of the performance appraisal. This paper aims at proposing an improved decision tree classification algorithm based on ID3 algorithm to raise the accuracy of early warning. The attribute selection measure of the improved ID3 algorithm is determined by information gain, the attribute significance and the number of attribute values, which not only overcomes the disadvantage of the gain criterion tends to favor attributes with many values of ID3 algorithm, but also considers the dependence between the attributes. The datasets used by experiments come from the Police Performance Appraisal Early Warning System and the UCI Machine Learning Repository respectively. The comparative analysis of the experimental results shows that the improved ID3 algorithm is more accurate and stable.
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