proc score

17 papers; 17 titles.

Back to keywords

Conference ×	Year ×	Title ×	Authors	Extras	Pages
MWSUG	2018	How to Score Big with SAS Solutions: Various Ways to Score New Data with Trained Models	Scott Koval		6
SGF	2017	Predictive Models: Storing, Scoring, and Evaluating	Matthew Duchnowski	source	10
SCSUG	2013	Using PROC STANDARD and PROC SCORE to impute missing multivariate values	Paul Montagna	source	8
SGF	2013	Bringing Churn Modeling Straight to the Source: SAS and Teradata In-Database Model Development	Jonathan Wexler, Karl Krycha	source	9
SGF	2013	Estimating Harrell's Optimism on Predictive Indices Using Bootstrap Samples	Irena Stijacic Cenzer, W. John Boscardin, Katharine Kirby, Yinghui Miao	source	12
SGF	2010	Using the Descriptor Portion of a SAS Data File	Dragos D. Capan	source	6
WUSS	2009	Automating the Process of Scoring a Generalized Linear Model Fitted using PROC GENMOD	Prakash Gurumurthy	source	9
WUSS	2009	Efficient Statistical Programming? - These Small Steps Make the Difference	Keiko I. Powers	source	16
SUGI	2005	Automating Predictive Analysis to Predict Medicare Fraud	Christine L. Warner	source	9
SESUG	2003	Advantages of PROC SCORE	Mark Tabladillo	source	2
SUGI	2001	Efficient Statistical Programming? - Let SAS Do the Work	Keiko I. Powers	source	4
WUSS	1998	The Capabilities of PROC FACTOR to Conduct an Exploratory Factor Analysis	Tyler C. Smith	source	6
SCSUG	1997	Contruction of Inptu for Environmental Simulation Models Using Multivariate Analysis	Joaquin Sanabria, Don Goss		18
NESUG	1994	A SAS Macro Incorporating Discriminant Analystis Techniques	Sivaram Kalyandrug, Antonis D. Koutsoukos, Lawrence V. Rubinstein		9
SEUGI	1993	Extensions to Multivariate Descriptive Analysis	Yves Roy	source	14
SUGI	1988	An Imputation System for a Large-Scale Survey	Eugene M. Burns, Doug Valcour	source	6
SUGI	1979	GLMM5 as a Tool for Simultaneous Study of the Structure of the Covariance Matrix and Experimental Design Effects	Ronald W. Helms, James D. Hosking, Keith E. Muller	source	4

Back to keywords