关键词: 互信息量, 平均互信息量, 分类模型, 影响因子, 样本预测信息

Abstract: Concerning the relevance between the attributes and the contribution difference of attribute values to attribute weights in classification dataset, an improved classification model and the formulas for calculating the impact factor and sample forecast information were proposed based on mutual information. And the classification model predicted the unlabelled object classes with the sample forecast information. Finally, the experimental results show that the classification model based on mutual information can effectively improve forecast precision and accuracy performance of classification algorithm.

Key words: mutual information, average mutual information, classification model, impact factor, sample forecast information