[Establishment of a quality evaluation method for Angelica different processed products from genuine producing areas based on data mining].

The paper reports the development of a quality evaluation method for Angelica different processed products. The data of high-performance liquid chromatography, water, total ash and extract were analyzed with SPSS Clementine 11.0 software. Discriminant analysis (DA) established the classification model and parameter for Angelica different processed products. Fish's discriminant functions of Angelica different processed products were generated using 8 predictor variables selected from 59 indexes. The correct rate of discriminating back substitution is 96.7%. Angelica different processed products can be accurately and reliably recognized and validated with DA of SPSS Clementine 11.0 software.