Data missing in data pretreatment has a serious
effect on the accuracy of subsequent analysis results in data
mining. In this paper, the cause of data missing and the
corresponding effect on data mining were discussed. Then the
missing pattern and the application limitation of traditional
missing value estimation were analyzed as well. Finally, the
estimation algorithm of missing value in MAR (missing at
random) pattern was mainly studied and applied in fault
classification based on wavelet neural network. The experiment
results show the efficiency of the algorithm.