caikit.interfaces.ts.data_model.timeseries_evaluation

The core data model object for a TimeSeries Evaluator.

Attributes

`log`
`error`

Classes

`Id`	A single instance of Id
`EvaluationRecord`	A single EvaluationRecord for EvaluationResult
`EvaluationResult`	EvaluationResult containing the evaluation results

Module Contents

caikit.interfaces.ts.data_model.timeseries_evaluation.log[source]

caikit.interfaces.ts.data_model.timeseries_evaluation.error

class caikit.interfaces.ts.data_model.timeseries_evaluation.Id[source]

Bases: caikit.core.DataObjectBase

A single instance of Id Representation of ids that can be either text or index. Customized this way to be able to work with repeated

value: py_to_proto.dataclass_to_proto.Annotated[str, OneofField('text'), FieldNumber(1)] | py_to_proto.dataclass_to_proto.Annotated[int, OneofField('index'), FieldNumber(2)]

class caikit.interfaces.ts.data_model.timeseries_evaluation.EvaluationRecord(id_values=None, metric_values=None, offset=None)[source]

Bases: caikit.core.DataObjectBase

A single EvaluationRecord for EvaluationResult Representation of EvaluationRecord for each row in the dataframe EvaluationRecord{id_values=[“A”, “B”], metric_values=[0.234, 0.568, 0.417], offset=”overall”}

id_values: py_to_proto.dataclass_to_proto.Annotated[List[Id], FieldNumber(1)]

metric_values: py_to_proto.dataclass_to_proto.Annotated[List[float], FieldNumber(2)]

offset: py_to_proto.dataclass_to_proto.Annotated[Id, FieldNumber(3)]

class caikit.interfaces.ts.data_model.timeseries_evaluation.EvaluationResult(records=None, id_cols=None, metric_cols=None, offset_col=None, df=None, producer_id=None)[source]

Bases: caikit.core.DataObjectBase

EvaluationResult containing the evaluation results Representation of EvaluationResult stores rows of the dataframe as list of records string lists to keep track of id and metric columns

records: py_to_proto.dataclass_to_proto.Annotated[List[EvaluationRecord], FieldNumber(1)]

id_cols: py_to_proto.dataclass_to_proto.Annotated[List[str], FieldNumber(2)]

metric_cols: py_to_proto.dataclass_to_proto.Annotated[List[str], FieldNumber(3)]

offset_col: py_to_proto.dataclass_to_proto.Annotated[str, FieldNumber(4)]

producer_id: py_to_proto.dataclass_to_proto.Annotated[caikit.core.data_model.ProducerId, FieldNumber(5)]

as_pandas() → pandas.DataFrame[source]: Generate and return a pandas DataFrame