HANA Polynomial Regression

Properties that can be configured for the HANA Polynomial Regression algorithm.

Syntax Use this algorithm to find the relationship between the independent variable and the dependent variable in a curvilinear fitted line.
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 Polynomial 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.
Degree of the Polynomial Enter the greatest exponent value of a polynomial expression.
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-created 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.