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SAS In-Memory Statistics

Title Level Training Formats
Predictive Modeling Using SAS In-Memory Statistics
This course focuses on the statistical and machine learning methods for predictive modeling available in the IMSTAT procedure. Topics include building candidate predictive models and assessing predictive models on training and holdout data for honest assessment using the IMSTAT procedure. You learn about methods such as decision trees and random forests using the DECISIONTREE and RANDOMWOODS statements. Modeling a binary response using the LOGISTIC and NEURAL statements is also covered, as is analyzing an interval target with generalized linear models using the GLM and GENMODEL statements. Generating and using Base SAS score code is demonstrated as well. Features of ODS Statistical Graphics are described for visualizing IMSTAT results.

3 Intermediate Classroom Live Web Classroom
Getting Started with SAS In-Memory Statistics
This course focuses on accessing data on the SAS LASR Analytic Server and performing exploratory analysis and preparation. Topics include starting the SAS LASR Analytic Server, loading data onto the LASR Analytic Server, and manipulating data on the LASR Analytic Server using the IMSTAT procedure. IMSTAT topics include deriving new temporary and permanent tables and columns as well as calculating summary statistics such as means, frequency, and percentiles. Creating filters and joins on in-memory data are also discussed.

3 Intermediate Classroom Live Web Classroom