Decision Tree that Subsequent Examples Score
call td_analyze ( 'decisiontree', 'database = val_source; tablename = customer_analysis; columns = income, age, nbr_children; dependent = gender; min_records = 2; max_depth = 5; binning = false; algorithm = gainratio; pruning = gainratio; outputdatabase = val_results; outputtablename = cust_analysis_dt; operatordatabase = val_user;' );
samplescoresize Parameter
call td_analyze ( 'decisiontreescore', 'samplescoresize = 10; database = val_source; tablename = customer_analysis; modeldatabase = val_results; modeltablename = cust_analysis_dt; outputdatabase = val_results; outputtablename = cust_analysis_dt_score; retain = city_name, state_code;' );
Produce Two Profile Tables
The two profile tables capture decision rules for each customer or prediction.
call td_analyze ( 'decisiontreescore', 'database = val_source; tablename = customer_analysis; modeldatabase = val_results; modeltablename = cust_analysis_dt; outputdatabase = val_results; outputtablename = cust_analysis_dt_score; retain = city_name, state_code; profiletables = true;' );
includeconfidence Parameter
The output table contains a column indicating how likely it is, for a particular leaf node in the tree, that the prediction is correct.
call td_analyze ( 'decisiontreescore', 'database = val_source; tablename = customer_analysis; modeldatabase = val_results; modeltablename = cust_analysis_dt; outputdatabase = val_results; outputtablename = cust_analysis_dt_score_conf; retain = city_name, state_code; includeconfidence = true;' );
targetedvalue Parameter
The output table contains a column indicating how likely it is, for a particular leaf node and binary targeted value, that the prediction is correct.
call td_analyze ( 'decisiontreescore', 'database = val_source; tablename = customer_analysis; modeldatabase = val_results; modeltablename = cust_analysis_dt; outputdatabase = val_results; outputtablename = cust_analysis_dt_score_target; retain = city_name, state_code; targetedvalue = F;' );
Confusion Matrix
A Confusion Matrix is an evaluation function.
call td_analyze ( 'decisiontreescore', 'database = val_source; tablename = customer_analysis; modeldatabase = val_results; modeltablename = cust_analysis_dt_m; outputdatabase = val_results; outputtablename = cust_analysis_dt_score_m; retain = city_name, state_code; scoringmethod = scoreandevaluate;' );