object_type#
- object_type()[source]#
Scientific type of the object.
Typing tag for all objects in
sktime
.String name:
"object_type"
Public metadata tag
Values: string or list of strings
Example:
"forecaster"
Example 2:
["transformer", "clusterer"]
(polymorphic object)Default:
"object"
In
sktime
, every object has a scientific type (scitype), determining the type of object and unified interface, e.g., forecaster, time series classifier, time series regressor.The
object_type
tag of an object is a string, or list of strings, specifying the scitpye of the object. For instance, a forecaster has scitype “forecaster”.In case of a list, the object is polymorphic, and can assume (class), or simultaneously satisfy different interfaces (object).
Valid scitypes are defined in
sktime.registry.BASE_CLASS_SCITYPE_LIST
, orsktime.registry.BASE_CLASS_REGISTER
.The full list of scitypes in the current version is:
"aligner"
: time series aligner or sequence aligner"classifier"
: time series classifier"clusterer"
: time series clusterer"dataset"
: dataset object"dataset_classification"
: classification dataset object"dataset_forecasting"
: forecasting dataset object"dataset_regression"
: regression dataset object"detector"
: detector - anomalies, outliers, change points"early_classifier"
: early time series classifier"estimator"
: estimator = object with fit"forecaster"
: time series forecaster"global_forecaster"
: global time series forecaster"metric"
: performance metric"metric_detection"
: performance metric for detectors"metric_forecasting"
: performance metric for point forecasting"metric_forecasting_proba"
: performance metric for probabilisticforecasting"network"
: deep learning network"object"
: base scitype for all objects"param_est"
: parameter fitting estimator"regressor"
: time series regressor"series-annotator"
: detector - anomalies, outliers, change points"splitter"
: time series splitter"transformer"
: time series transformer"transformer-pairwise"
: pairwise transformer for tabular data, distance or kernel"transformer-pairwise-panel"
: pairwise transformer for panel data, distance or kernel"distribution"
: pandas-like probability distribution