abacusai.api_class.batch_prediction
Module Contents
Classes
Helper class that provides a standard way to create an ABC using |
|
Batch Prediction Config for the PREDICTIVE_MODELING problem type |
|
Helper class that provides a standard way to create an ABC using |
- class abacusai.api_class.batch_prediction.BatchPredictionArgs
Bases:
abacusai.api_class.abstract.ApiClass
Helper class that provides a standard way to create an ABC using inheritance.
- problem_type: abacusai.api_class.enums.ProblemType
- class abacusai.api_class.batch_prediction.PredictiveModelingBatchPredictionArgs
Bases:
BatchPredictionArgs
Batch Prediction Config for the PREDICTIVE_MODELING problem type :param for_eval: If True, the test fold which was created during training and used for metrics calculation will be used as input data. These predictions are hence, used for model evaluation. :type for_eval: bool :param explainer_type: The type of explainer to use to generate explanations on the batch prediction. :type explainer_type: enums.ExplainerType :param number_of_samples_to_use_for_explainer: Number Of Samples To Use For Kernel Explainer. :type number_of_samples_to_use_for_explainer: int :param include_multi_class_explanations: If True, Includes explanations for all classes in multi-class classification. :type include_multi_class_explanations: bool :param features_considered_constant_for_explanations: Comma separate list of fields to treat as constant in SHAP explanations. :type features_considered_constant_for_explanations: str :param importance_of_records_in_nested_columns: Returns importance of each index in the specified nested column instead of SHAP column explanations. :type importance_of_records_in_nested_columns: str :param explanation_filter_lower_bound: If set explanations will be limited to predictions above this value, Range: [0, 1]. :type explanation_filter_lower_bound: float :param explanation_filter_upper_bound: If set explanations will be limited to predictions below this value, Range: [0, 1]. :type explanation_filter_upper_bound: float :param bound_label: For classification problems specifies the label to which the explanation bounds are applied. :type bound_label: str :param output_columns: A list of column names to include in the prediction result. :type output_columns: list
- explainer_type: abacusai.api_class.enums.ExplainerType
- __post_init__()
- class abacusai.api_class.batch_prediction._BatchPredictionArgsFactory
Bases:
abacusai.api_class.abstract._ApiClassFactory
Helper class that provides a standard way to create an ABC using inheritance.
- config_abstract_class
- config_class_key = 'problemType'
- config_class_map