This thesis presents a data generalization algorithm based on data cube. The algorithm can clean the data for data mining and im-prove efficiency of data mining.
该文提出了一种基于数据立方体的数据泛化算法用于数据预处理，能够为数据挖掘提供良好的数据环境，提高数据挖掘的有效性。
After speed of statistical convergence and MSE (Mean Square Error) of these algorithms are compared, Bayes Generalization algorithm is assessed to be the most appropriate.
在比较收敛速度和均方差后，确定选用贝叶斯正则算法建立模型。
After speed of statistical convergence and MSE (Mean Square Error) of these algorithms are compared, Bayes Generalization algorithm is assessed to be the most appropriate.
在比较收敛速度和均方差后，确定选用贝叶斯正则算法建立模型。
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