This operator searches for anomalies in a sequence in comparison to the learned sequences. To do this, the operator uses the deviation information created by the DeviationSequenceLearn operator. For each tuple of a sequence, the value is compared to the learned distribution (mean and standard deviation). The data input port is 0, the input port with learn data is 1.
- interval Defines, how many standard deviations are allowed for a tuple to be different from the mean. 3.0 is the default value. Choose a smaller value to get more anomalies
- tupleCountLearnAttribute The attribute name on the learn port that gives the group count (the counter that gives each tuple in the sequence a number)
- meanLearnAttribute The attribute name on the learn port that has the mean
- standardDeviationLearnAttribute The attribute name on the learn port that has the standard deviation
- valueDataAttribute Name of the attribute which should be analysed
- GROUP_BY If you use a deviationSequenceLearn operator, use 'group' as grouping attribute.
- fastGrouping Use hash code instead of tuple compare to create group. Potentially unsafe!
The DeviationSequenceAnomalyDetection operator uses the learned data from the previous DeviationSequenceLearn operator.