\u003cp\u003e\u003cb\u003eAdvance your skills in building predictive models with SAS!\u003c/p\u003e\u003c/b\u003e\u003cp\u003e\u003ci\u003eBuilding Regression Models with SAS: A Guide for Data Scientists\u003c/i\u003e 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:\u003c/p\u003e\u003cul\u003e\u003cli\u003egeneral linear models\u003cli\u003equantile regression models\u003cli\u003elogistic regression models\u003cli\u003egeneralized linear models\u003cli\u003egeneralized additive models\u003cli\u003eproportional hazards regression models\u003cli\u003etree models\u003cli\u003emodels based on multivariate adaptive regression splines\u003c/ul\u003e\u003cp\u003e\u003ci\u003eBuilding Regression Models with SAS\u003c/i\u003e is an essential guide to learning about a variety of models that provide interpretability as well as predictive performance.\u003c/p\u003e
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