trendminer_experimental.anomaly_detection.exceptions module¶

The exceptions thrown by the model trainer.

exception trendminer_experimental.anomaly_detection.exceptions.DuplicateVariableNamesException¶

Bases: Exception

If duplicates are passed for variables names in a PMML model

exception trendminer_experimental.anomaly_detection.exceptions.NotFittedException¶

Bases: Exception

The model is not fitted yet

exception trendminer_experimental.anomaly_detection.exceptions.WrongNumberOfDimensionsException¶

Bases: Exception

Dimension of input dataframe (dim) must be 2<=dim<=10

exception trendminer_experimental.anomaly_detection.exceptions.WrongNumberOfVariableNamesException¶

Bases: Exception

If the provided list of variable names does not match the number of variables in the model

exception trendminer_experimental.anomaly_detection.exceptions.WrongValueForThresholdException¶

Bases: Exception

Value of threshold must be 0<=dim<=1