HANA Variance Test

Properties that can be configured for the HANA Variance Test algorithm.

Syntax HANA Variance test identifies the outliers in a set of numerical data. The lower boundary and upper boundary for the data are calculated based on the mean and the standard deviation of data and the multiplier value provided by you.

The multiplier is a double type coefficient, which helps you to test whether all the values of a numerical vector are in the range.

If a value is outside the range, this suggests that it does not pass the variance test and the value is therefore marked as an outlier.

Note Creating models using the HANA Anomaly Detection algorithm is not supported.
HANA Variance Test Properties
Table 1: Algorithm Properties
Property Description
Output mode Select the mode in which you want to use the output of this algorithm.
  • Show Outliers: Adds a Boolean column to the input data specifying if the corresponding value is an outlier.
  • Remove Outliers: Removes outlying values from the input data.
Independent Columns Select the input source columns.
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.
Multiplier Enter the multiplier value to decide the range of lower and upper boundaries, which helps in identifying the outliers. The default value is 3.0.
Note Input must be a positive integer value.
Number of Threads Enter the number of threads that the algorithm should use during execution.
Predicted Column Name Enter a name for the new column that contains the predicted values.