摘要
This article deals with implementation of the classification and regression trees into the DMAIC phases of Six Sigma methodology. Six Sigma methodology seeks to improve the quality of manufacturing process by identifying and minimizing variability of this process. Using the classification, regression and segmentation trees as a part of the Data Mining methods could improve results of DMAIC phases. This improvement has a direct impact on the Sigma performance level of processes. The author introduces research results of implementation Data Mining algorithms into retail sales promotion. The author implements classification and regression techniques in our research. As a software tool has been selected SPSS PASW Modeler. The author deals with more data mining algorithms ad their implementation in the DMAIC phases. The article is divided into several parts. The first part is the introduction to Six Sigma methodology, the second deals with classification and regression trees. The third part describes tree research focused on the implementation of data mining algorithms and the fourth section summarizes the research results.
