Which forecasting algorithms do not leverage the SAP HANA Predictive Analysis Library?

The correct choice points to the Time-Series forecasting algorithms as those that do not utilize the SAP HANA Predictive Analysis Library.

Time-Series forecasting techniques include methods based on historical data points collected over time. While they can be sophisticated and involve models that account for various patterns (like trends and seasonality), these methods are generally more traditional and often rely on simpler statistical approaches rather than advanced predictive analytics provided by dedicated libraries. In contrast, regression analysis and other advanced forecasting algorithms typically take advantage of the capabilities offered by the SAP HANA Predictive Analysis Library to improve accuracy and performance.

Moving averages and accuracy measurements are also less intensive and do not typically require the advanced data processing available through the library. However, they are often employed in conjunction with other predictive algorithms to enhance results. Thus, while they are utilized in different contexts, the Time-Series methods stand out as not leveraging the predictive capabilities offered by SAP HANA.