tempor.datasources.prediction.temporal.plugin_uci_diabetes module¶
Module defining the UCI diabetes data source.
-
class tempor.datasources.prediction.temporal.plugin_uci_diabetes.UCIDiabetesDataSource(make_regular: bool =
False, use_int_index: bool =True, targets: tuple[str, ...] =('hypoglycemic_symptoms',), **kwargs: Any)[source]¶ Bases:
TemporalPredictionDataSourceUCI diabetes data source.
See: https://archive.ics.uci.edu/ml/machine-learning-databases/diabetes
- Parameters:¶
- make_regular : bool, optional¶
Whether to reindex the dataset to have regular timesteps. Defaults to
False.- use_int_index : bool, optional¶
Whether to use integer index. Defaults to
True.- targets : Tuple[str, ...], optional¶
The target feature(s). Defaults to
("hypoglycemic_symptoms",).- **kwargs : Any
Any additional keyword arguments will be passed to parent constructor.
- static dataset_dir() str[source]¶
The path to the directory where the data file(s) will be stored, if relevant. If the data source has no data files, return
None.Note
the path should correspond to a subdirectory within
data_root_dir.
- load(**kwargs: Any) TemporalPredictionDataset[source]¶
The method that should return a temporal prediction dataset.
-
category : ClassVar[plugin_typing.PluginCategory] =
'prediction.temporal'¶ Plugin category, such as
'prediction.one_off.classification'. Must be set by the plugin class using@register_plugin.
-
name : ClassVar[plugin_typing.PluginName] =
'uci_diabetes'¶ Plugin name, such as
'my_nn_classifier'. Must be set by the plugin class using@register_plugin.
-
plugin_type : ClassVar[plugin_typing.PluginTypeArg] =
'datasource'¶ Plugin type, such as
'method'. May be optionally set by the plugin class using@register_plugin, else will set the default plugin type.