Exceptions =========================== .. py:module:: evalml.exceptions .. autoapi-nested-parse:: Exceptions used in EvalML. Submodules ---------- .. toctree:: :titlesonly: :maxdepth: 1 exceptions/index.rst Package Contents ---------------- Classes Summary ~~~~~~~~~~~~~~~ .. autoapisummary:: evalml.exceptions.PartialDependenceErrorCode evalml.exceptions.PipelineErrorCodeEnum evalml.exceptions.ValidationErrorCode Exceptions Summary ~~~~~~~~~~~~~~~~~~ .. autoapisummary:: `evalml.exceptions.AutoMLSearchException` `evalml.exceptions.ComponentNotYetFittedError` `evalml.exceptions.DataCheckInitError` `evalml.exceptions.MethodPropertyNotFoundError` `evalml.exceptions.MissingComponentError` `evalml.exceptions.NoPositiveLabelException` `evalml.exceptions.NullsInColumnWarning` `evalml.exceptions.ObjectiveCreationError` `evalml.exceptions.ObjectiveNotFoundError` `evalml.exceptions.ParameterNotUsedWarning` `evalml.exceptions.PartialDependenceError` `evalml.exceptions.PipelineError` `evalml.exceptions.PipelineNotFoundError` `evalml.exceptions.PipelineNotYetFittedError` `evalml.exceptions.PipelineScoreError` Contents ~~~~~~~~~~~~~~~~~~~ .. py:exception:: AutoMLSearchException Exception raised when all pipelines in an automl batch return a score of NaN for the primary objective. .. py:exception:: ComponentNotYetFittedError An exception to be raised when predict/predict_proba/transform is called on a component without fitting first. .. py:exception:: DataCheckInitError Exception raised when a data check can't initialize with the parameters given. .. py:exception:: MethodPropertyNotFoundError Exception to raise when a class is does not have an expected method or property. .. py:exception:: MissingComponentError An exception raised when a component is not found in all_components(). .. py:exception:: NoPositiveLabelException Exception when a particular classification label for the 'positive' class cannot be found in the column index or unique values. .. py:exception:: NullsInColumnWarning Warning thrown when there are null values in the column of interest. .. py:exception:: ObjectiveCreationError Exception when get_objective tries to instantiate an objective and required args are not provided. .. py:exception:: ObjectiveNotFoundError Exception to raise when specified objective does not exist. .. py:exception:: ParameterNotUsedWarning(components) Warning thrown when a pipeline parameter isn't used in a defined pipeline's component graph during initialization. .. py:exception:: PartialDependenceError(message, code) Exception raised for all errors that partial dependence can raise. :param message: descriptive error message :type message: str :param code: code for speicific error :type code: PartialDependenceErrorCode .. py:class:: PartialDependenceErrorCode Enum identifying the type of error encountered in partial dependence. **Attributes** .. list-table:: :widths: 15 85 :header-rows: 0 * - **ALL_OTHER_ERRORS** - all_other_errors * - **COMPUTED_PERCENTILES_TOO_CLOSE** - computed_percentiles_too_close * - **FEATURE_IS_ALL_NANS** - feature_is_all_nans * - **FEATURE_IS_MOSTLY_ONE_VALUE** - feature_is_mostly_one_value * - **FEATURES_ARGUMENT_INCORRECT_TYPES** - features_argument_incorrect_types * - **ICE_PLOT_REQUESTED_FOR_TWO_WAY_PLOT** - ice_plot_requested_for_two_way_partial_dependence_plot * - **INVALID_CLASS_LABEL** - invalid_class_label_requested_for_plot * - **INVALID_FEATURE_TYPE** - invalid_feature_type * - **PIPELINE_IS_BASELINE** - pipeline_is_baseline * - **TOO_MANY_FEATURES** - too_many_features * - **TWO_WAY_REQUESTED_FOR_DATES** - two_way_requested_for_dates * - **UNFITTED_PIPELINE** - unfitted_pipeline **Methods** .. autoapisummary:: :nosignatures: evalml.exceptions.PartialDependenceErrorCode.name evalml.exceptions.PartialDependenceErrorCode.value .. py:method:: name(self) The name of the Enum member. .. py:method:: value(self) The value of the Enum member. .. py:exception:: PipelineError(message, code, details=None) Exception raised for errors that can be raised when applying a pipeline. :param message: descriptive error message :type message: str :param code: code for specific error :type code: PipelineErrorCodeEnum :param details: additional details for error :type details: dict .. py:class:: PipelineErrorCodeEnum Enum identifying the type of error encountered while applying a pipeline. **Attributes** .. list-table:: :widths: 15 85 :header-rows: 0 * - **PREDICT_INPUT_SCHEMA_UNEQUAL** - predict_input_schema_unequal **Methods** .. autoapisummary:: :nosignatures: evalml.exceptions.PipelineErrorCodeEnum.name evalml.exceptions.PipelineErrorCodeEnum.value .. py:method:: name(self) The name of the Enum member. .. py:method:: value(self) The value of the Enum member. .. py:exception:: PipelineNotFoundError An exception raised when a particular pipeline is not found in automl search results. .. py:exception:: PipelineNotYetFittedError An exception to be raised when predict/predict_proba/transform is called on a pipeline without fitting first. .. py:exception:: PipelineScoreError(exceptions, scored_successfully) An exception raised when a pipeline errors while scoring any objective in a list of objectives. :param exceptions: A dictionary mapping an objective name (str) to a tuple of the form (exception, traceback). All of the objectives that errored will be stored here. :type exceptions: dict :param scored_successfully: A dictionary mapping an objective name (str) to a score value. All of the objectives that did not error will be stored here. :type scored_successfully: dict .. py:class:: ValidationErrorCode Enum identifying the type of error encountered in holdout validation. **Attributes** .. list-table:: :widths: 15 85 :header-rows: 0 * - **INVALID_HOLDOUT_GAP_SEPARATION** - invalid_holdout_gap_separation * - **INVALID_HOLDOUT_LENGTH** - invalid_holdout_length **Methods** .. autoapisummary:: :nosignatures: evalml.exceptions.ValidationErrorCode.name evalml.exceptions.ValidationErrorCode.value .. py:method:: name(self) The name of the Enum member. .. py:method:: value(self) The value of the Enum member.