Properties that can be configured for the HANA Exponential Regression
algorithm.
Syntax Use this algorithm to find trends
in data. This algorithm performs univariate regression analysis. It determines
how an individual variable influences another variable using an exponential
function.
HANA Exponential Regression properties
Note The data type of columns used during model
scoring should be same as the data type of columns used while building the
model.
Table 1:
Algorithm Properties
| Property |
Description |
| Output Mode |
Select the mode in which you want to use the output of this
algorithm. Possible values: - Fill: Fills missing values in the target column.
- Trend: Predicts the values for the dependent column and
adds an extra column in the output containing the
predicted values.
|
| Independent Columns |
Select the input columns with which you want to perform the
regression analysis. |
| Dependent Column |
Select the target column for which you want to perform the
regression analysis. |
| Missing Values |
Select the method for handling missing values. Possible
methods: - Ignore: The algorithm skips the
records containing missing values in the independent or
dependent columns.
- Keep: The algorithm retains the
records containing missing values during calculation.
|
| Predicted Column Name |
Enter a name for the newly-added column that contains the
predicted values. |
| Number of Threads |
Enter the number of threads that the algorithm should use during
execution. The default value is 1. |