Logarithmic Regression

Properties that can be configured for the Logarithmic 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 a logarithmic function 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.
Logarithmic 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 methods:
  • 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.