Considering the inherent feature of factor data

the Naive Bayes classifier

which makes the assumption that numeric attributes are generated by a single Normal distribution

is adopted.The classification performance of factor data sets is studied both before and after dimension reduction.Experimental results show that the statistic value of Kaiser-Meyer-Olkin(KMO) and the communalities of factor analysis are related with classification accuracy.When the value of KMO is larger than 0.8 and the little part of communalities are smaller than 80%

it is appropriated for the classification to use factor analysis as dimension reduction method.