Log-likelihood analysis
Introduction
Since version 7.23
Log-likelihood analysis evaluates the effect of different subsets of evidence on the Log-likelihood.
Log-likelihood values are often used for Anomaly detection.
Log-likelihood analysis can be used to:
- See which individual pieces of evidence change the log-likelihood the most
- See which individual pieces of evidence, when excluded, change the log-likelihood the most
- See which subsets of evidence which, when included or excluded, change the log-likelihood the most.
Support
| Variable type | Evidence |
|---|---|
| Discrete | Yes |
| Continuous | Yes |
| Hybrid | Yes |
We use the term None to refer to the case when none of the evidence (being analyzed) is included. We use the term All to refer to the case when all of the evidence (being analyzed) is included.
Subsets
The subsets to consider are generated by looking at all possible combinations of evidence, subject to the following constraints.
Max evidence subset size
The number of items of evidence in each subset.
Subset method
When Subset method is set to Include, evidence on variables in the subset is included, but not other evidence variables (being analyzed).
When Subset method is set to Exclude, all evidence is used, except for those in the subset.