SAP HANA Predictive Analysis Library (PAL)

Related Information
SAP HANA Smart Data Streaming: Developer Guide
3.3 Regression Algorithms
This section describes the regression algorithms that are provided by the Predictive Analysis Library.
3.3.1 Bi-Variate Geometric Regression
Geometric regression is an approach used to model the relationship between a scalar variable y and a variable
denoted X. In geometric regression, data is modeled using geometric functions, and unknown model
parameters are estimated from the data. Such models are called geometric models.
In PAL, the implementation of geometric regression is to transform to linear regression and solve it:
y = β 0 × x β 1
Where β 0 and β 1 are parameters that need to be calculated.
The steps are:
1. Put natural logarithmic operation on both sides: ln(y) = ln(β 0 × x β 1 )
2. Transform it into: ln(y) = ln( β 0 ) + β 1 × ln(x)
3. Let y' = ln(y), x' = ln(x), β 0 ' = ln(β 0 )
y' = β 0 ' + β 1 × x'
Thus, y’ and x’ is a linear relationship and can be solved with the linear regression method.
The implementation also supports calculating the F value and R^2 to determine statistical significance.
Prerequisites
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No missing or null data in the inputs.
The data is numeric, not categorical.
GEOREGRESSION
This is a geometric regression function.
SAP HANA Predictive Analysis Library (PAL)
PAL Functions P U B L I C 241