SAP HANA Predictive Analysis Library (PAL)

Related Information
SAP HANA Smart Data Streaming: Developer Guide
3.2 Classification Algorithms
This section describes the classification algorithms that are provided by the Predictive Analysis Library.
3.2.1 Area Under Curve (AUC)
Area under curve (AUC) is a traditional method to evaluate the performance of classification algorithms.
Basically, it can evaluate the binary classifier, but can be extended to multiple-class condition easily.
In an area under curve algorithm, curve is the receiver operating characteristic (ROC) curve. The curve can be
obtained by plotting the true positive rate (TPR) against the false positive rate (FPR) at several threshold. The
calculation formulas are listed below.
Where:
TP: true positive
FN: false negative
FP: false positive
TN: true negative
After plotting the ROC curve, you can calculate the area under the curve by using numerical integral
algorithms such as Simpson’s rule. The value of AUC ranges from 0.5 to 1. If the AUC equals to 1, the classifier
is expected to have perfect performance.
Prerequisite
No missing or null data in the inputs.
118 P U B L I C
SAP HANA Predictive Analysis Library (PAL)
PAL Functions