SAP HANA Predictive Analysis Library (PAL)

When VERBOSE_OUTPUT is set to 1:
3.2.11 Parameter Selection and Model Evaluation (PSME)
Parameter selection and model evaluation (PSME) is used to enable cross validation and parameter selection
for some PAL functions.
To avoid over fitting, it is a common practice to take use of cross validation to evaluate model performance
and perform model selection for the optimal parameters of the model. This algorithm is an envelope for
different classification algorithms to provide automatic parameter selection and model evaluation facilities
during training phase. Logistic regression, naive Bayes, support vector machine (SVM), and random forest are
supported.
PSME
This function performs parameter selection and model evaluation for classification algorithms including
logistic regression, naive Bayes, and support vector machine (SVM).
Procedure Generation
CALL SYS.AFLLANG_WRAPPER_PROCEDURE_CREATE (‘AFLPAL’, ‘PSME’, ‘’,
'', );
The signature table should contain the following records:
Table 147:
Position Schema Name Table Type Name Parameter Type
1
IN
2 IN
3 IN
202 P U B L I C
SAP HANA Predictive Analysis Library (PAL)
PAL Functions