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I'm trying to use SAS from more of a machine learning perspective than a pure stats perspective. I want to perform resampling on a dataset to measure the predictive accuracy of a LDA and Logistic Regression. However, when I perform proc logistic or proc discrim all SAS seems to output is a bunch of statistical measures. I want to use the models to predict the output of my test dataset. Is there any way to do this in SAS?

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Section 4.4 in the SAS course notes on Multivariate Statistical Methods: Practical Research Applications there are examples for empirical validation and scoring.

You'd want to consider using the testlist or testout options for example using proc discrim

proc discrim data = old-data testdata = new-data testlist;
class variabls;
priors priors;
var variables;
run;

or

proc discrim data = old-data testdata = new-data testout = scored-data;
class variable;
priors priors;
var variables;
run;

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You should look into the OUTPUT statements on both those PROCs, and also look at the SCORE statement, for using a model on new data. More on SCORE from SAS: http://support.sas.com/rnd/app/da/new/801ce/stat/chap4/sect11.htm

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