MissingPredictionTreatment

The missing prediction treatment options are used when at least one model for which the predicate in the Segment evaluates to true has a missing result. The attribute missingThreshold is closely related and has default value 1. The options are defined as follows:

• returnMissing means that if at least one model has a missing result, the whole MiningModel's result should be missing.
• skipSegment says that if a model has a missing result, that segment is ignored and the results are computed based on other segments. However, if the fraction of the models with missing results ( weighted if the model combination method is weighted ) exceeds the missingThreshold, the returned result must be missing. This option should not be used with modelChain combination method.
• continue says that if a model has a missing result, the processing should continue normally. This can work well for voting or modelChain situations, as well as returnFirst and returnAll. In case of majorityVote or weightedMajorityVote the missing result can be returned if it gets the most ( possibly weighted ) votes, or if the fraction of the models with missing result exceeds the missingThreshold. Otherwise a valid result is computed normally. Other model combination methods will return a missing value as the result.