a non-empty list of ModelIdentity instances of submodels that failed to produce a prediction. Since the top-level model must fail in order for an EitherAuditorError to be returned, this is a non-empty list. This non-empty list is in DFS preorder.
messages indicating errors encountered.
names of variables with missing data encountered in the model computation.
messages indicating errors encountered.
a non-empty list of ModelIdentity instances of submodels that failed to produce a prediction.
a non-empty list of ModelIdentity instances of submodels that failed to produce a prediction. Since the top-level model must fail in order for an EitherAuditorError to be returned, this is a non-empty list. This non-empty list is in DFS preorder.
names of variables with missing data encountered in the model computation.
Diagnostic information about failures encountered. This structure can be thought of as a flattened tree of failures. The tree is pruned one of two ways, it is either prune at the root, or pruned at the the first submodel successes encountered. The tree is pruned at the root if the auditor is created via
EitherAuditor[A](aggregateDiagnostics = false)
.If the auditor is created via
EitherAuditor[A](aggregateDiagnostics = true)
, or simplyEitherAuditor[A]
, then the trees are pruned at successes. For instance, imagine a model, model1
, that has submodels2
and5
. Submodel2
has submodels3
and4
; submodel5
has submodels6
and7
. Let's say the following submodels fail: 1, 2, 4, 6, 7. Then, information would be aggregated as follows:Notice because submodel
5
succeeds, error information about submodels6
and7
is disregarded because submodel5
could recover from its submodels' errors.So, in the event that diagnostics are aggregated, only information about submodels
1
,2
,4
should be contained in the EitherAuditorError returned by the EitherAuditor.a non-empty list of ModelIdentity instances of submodels that failed to produce a prediction. Since the top-level model must fail in order for an EitherAuditorError to be returned, this is a non-empty list. This non-empty list is in DFS preorder.
messages indicating errors encountered.
names of variables with missing data encountered in the model computation.