EBOOK
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Advance your skills in building predictive models with SAS!
Building Regression Models with SAS: A Guide for Data Scientists teaches data scientists, statisticians, and other analysts who use SAS to train regression models for prediction with large, complex data. Each chapter focuses on a particular model and includes a high-level overview, followed by basic concepts, essential syntax, and examples using new procedures in both SAS/STAT and SAS Viya. By emphasizing introductory examples and interpretation of output, this book provides readers with a clear understanding of how to build the following types of models:
• general linear models
• quantile regression models
• logistic regression models
• generalized linear models
• generalized additive models
• proportional hazards regression models
• tree models
• models based on multivariate adaptive regression splines
Building Regression Models with SAS is an essential guide to learning about a variety of models that provide interpretability as well as predictive performance.
Building Regression Models with SAS: A Guide for Data Scientists teaches data scientists, statisticians, and other analysts who use SAS to train regression models for prediction with large, complex data. Each chapter focuses on a particular model and includes a high-level overview, followed by basic concepts, essential syntax, and examples using new procedures in both SAS/STAT and SAS Viya. By emphasizing introductory examples and interpretation of output, this book provides readers with a clear understanding of how to build the following types of models:
• general linear models
• quantile regression models
• logistic regression models
• generalized linear models
• generalized additive models
• proportional hazards regression models
• tree models
• models based on multivariate adaptive regression splines
Building Regression Models with SAS is an essential guide to learning about a variety of models that provide interpretability as well as predictive performance.