Properties that can be configured for the HANA R-Multiple Linear Regression
algorithm.
Syntax Use this algorithm to find the
linear relationship between a dependent variable and one or more independent
variables.
Note The data type of columns used during model
scoring should be same as the data type of columns used while building the
model.
HANA R-Multiple Linear Regression Properties
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 ignores the records containing
missing values in the independent or dependent columns.
- Keep: The algorithm retains the records containing
missing values during calculation.
- Stop: The algorithm stops the execution if a value is
missing in the independent column or the dependent
column.
|
| Confidence Level |
Enter the confidence level of the algorithm (the accuracy of
predictions). The default value is 0.95. |
| Predicted Column Name |
Enter a name for the newly-created column that contains the
predicted values. |