proc cas; decisionTree.forestTrain / table={name="class", caslib="casuser"} target="Sex" inputs={"Height", "Weight"}; run;
proc cas; decisionTree.forestTrain / table={name="class", caslib="casuser"} target="Weight" inputs={"Height", "Age"} nTree=100 seed=12345 varImp=TRUE oob=TRUE saveState={name="forest_astore", caslib="casuser", replace=TRUE}; run;
proc cas; simple.freq / table={name="cars", caslib="casuser"} inputs={"Type"}; run;
proc cas; simple.freq / table={name="cars", caslib="casuser", groupBy={"Type"}} inputs={"Origin"} includeMissing=true casOut={name="freq_results", caslib="casuser", replace=true}; run;
proc cas; decisionTree.gbtreeScore / modelTable={name='myGradientBoostModel', caslib='models'}, table={name='inputData', caslib='public'}, casOut={name='scoredDataWithDetails', replace=True}, copyVars={'customer_id', 'feature1', 'feature2'}, assess=True, encodeName=True; r...
proc cas; langModel.IdentifySpeakers / casOut={name='detailed_speaker_output', replace=TRUE}, table={name='my_audio_table', caslib='my_audio_lib'}, model={ name='my_speaker_model', caslib='my_model_lib', gpu={devices={0, 1}}} , minSpeak...
proc cas; mps_string = " NAME A_MORE_COMPLEX_PROBLEM ROWS N TOTAL_PROFIT L RESOURCE_LIMIT_A L RESOURCE_LIMIT_B COLUMNS PRODUCT_ONE TOTAL_PROFIT 150.0 RESOURCE_LIMIT_A 10.0 PRODUCT_ONE RESOURCE_LIMIT_B 25.0 PRODUCT_TWO TOTAL_PROFIT 175.0 RESOURCE_LIM...
proc cas; textRuleScore.loadTableFromDisk / path='/path/to/your/models/categories.mco' casOut={name='category_model', caslib='casuser', replace=true, promote=true, label='My Category Model for Scoring'}; run;
proc cas; table.loadTable / caslib='CASUSER' path='cars.csv' casOut={name='CARS_TABLE'}; run;
proc cas; table.loadTable / caslib='CASUSER' path='cars.csv' casOut={name='CARS_GLOBAL', label='Global Cars Data', promote=TRUE} importOptions={fileType='CSV'}; run;