Properties that can be configured for the Linear 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 with the least square
methodology.
Note The data type of columns used during model
scoring should be same as the data type of columns used while building the
model.
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 Column |
Select the input column 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
values: - Ignore: The algorithm skips the records containing
missing values in the independent or dependent columns.
- Stop: The algorithm stops the execution if a value is
missing in the independent column or the dependent
column.
|
| Predicted Column Name |
Enter a name for the newly-created column that contains the
predicted values. |