Detail kurzu

Applied Analytics Using SAS(R) Enterprise Miner(TM)

EDU Trainings s.r.o.

Popis kurzu

This course covers the skills that are required to assemble analysis flow diagrams using the rich tool set of SAS Enterprise Miner for both pattern discovery (segmentation, association, and sequence analyses) and predictive modeling (decision tree, regression, and neural network models). This course is appropriate for SAS Enterprise Miner 5.3 up to the current release.

Obsah kurzu

IntroductionIntroduction to SAS Enterprise Miner.Accessing and Assaying Prepared DataCreating a SAS Enterprise Miner project, library, and diagram.Defining a data source.Exploring a data source.Introduction to Predictive Modeling: Predictive Modeling Fundamentals and Decision TreesIntroduction.Cultivating decision trees.Optimizing the complexity of decision trees.Understanding additional diagnostic tools (self-study).Autonomous tree growth options (self-study).Introduction to Predictive Modeling: RegressionsSelecting regression inputs.Optimizing regression complexity.Interpreting regression models.Transforming inputs.Categorical inputs.Polynomial regressions (self-study).Introduction to Predictive Modeling: Neural Networks and Other Modeling ToolsInput selection.Stopped training.Other modeling tools (self-study).Model AssessmentModel fit statistics.Statistical graphics.Adjusting for separate sampling.Profit matrices.Model ImplementationInternally scored data sets.Score code modules.Introduction to Pattern DiscoveryCluster analysis.Market basket analysis (self-study).Special TopicsEnsemble models.Variable selection.Categorical input consolidation.Surrogate models.SAS Rapid Predictive Modeler.Case StudiesBanking segmentation case study.Website usage associations case study.Credit risk case study.Enrollment management case study.

Cílová skupina

Data analysts, qualitative experts, and others who want an introduction to SAS Enterprise Miner
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