exceptions#

Exceptions used in EvalML.

Module Contents#

Classes Summary#

PartialDependenceErrorCode

Enum identifying the type of error encountered in partial dependence.

PipelineErrorCodeEnum

Enum identifying the type of error encountered while applying a pipeline.

ValidationErrorCode

Enum identifying the type of error encountered in holdout validation.

Exceptions Summary#

Contents#

exception evalml.exceptions.exceptions.AutoMLSearchException[source]#

Exception raised when all pipelines in an automl batch return a score of NaN for the primary objective.

exception evalml.exceptions.exceptions.ComponentNotYetFittedError[source]#

An exception to be raised when predict/predict_proba/transform is called on a component without fitting first.

exception evalml.exceptions.exceptions.DataCheckInitError[source]#

Exception raised when a data check can’t initialize with the parameters given.

exception evalml.exceptions.exceptions.MethodPropertyNotFoundError[source]#

Exception to raise when a class is does not have an expected method or property.

exception evalml.exceptions.exceptions.MissingComponentError[source]#

An exception raised when a component is not found in all_components().

exception evalml.exceptions.exceptions.NoPositiveLabelException[source]#

Exception when a particular classification label for the ‘positive’ class cannot be found in the column index or unique values.

exception evalml.exceptions.exceptions.NullsInColumnWarning[source]#

Warning thrown when there are null values in the column of interest.

exception evalml.exceptions.exceptions.ObjectiveCreationError[source]#

Exception when get_objective tries to instantiate an objective and required args are not provided.

exception evalml.exceptions.exceptions.ObjectiveNotFoundError[source]#

Exception to raise when specified objective does not exist.

exception evalml.exceptions.exceptions.ParameterNotUsedWarning(components)[source]#

Warning thrown when a pipeline parameter isn’t used in a defined pipeline’s component graph during initialization.

exception evalml.exceptions.exceptions.PartialDependenceError(message, code)[source]#

Exception raised for all errors that partial dependence can raise.

Parameters
class evalml.exceptions.exceptions.PartialDependenceErrorCode[source]#

Enum identifying the type of error encountered in partial dependence.

Attributes

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

name

The name of the Enum member.

value

The value of the Enum member.

name(self)#

The name of the Enum member.

value(self)#

The value of the Enum member.

exception evalml.exceptions.exceptions.PipelineError(message, code, details=None)[source]#

Exception raised for errors that can be raised when applying a pipeline.

Parameters
  • message (str) – descriptive error message

  • code (PipelineErrorCodeEnum) – code for specific error

  • details (dict) – additional details for error

class evalml.exceptions.exceptions.PipelineErrorCodeEnum[source]#

Enum identifying the type of error encountered while applying a pipeline.

Attributes

PREDICT_INPUT_SCHEMA_UNEQUAL

predict_input_schema_unequal

Methods

name

The name of the Enum member.

value

The value of the Enum member.

name(self)#

The name of the Enum member.

value(self)#

The value of the Enum member.

exception evalml.exceptions.exceptions.PipelineNotFoundError[source]#

An exception raised when a particular pipeline is not found in automl search results.

exception evalml.exceptions.exceptions.PipelineNotYetFittedError[source]#

An exception to be raised when predict/predict_proba/transform is called on a pipeline without fitting first.

exception evalml.exceptions.exceptions.PipelineScoreError(exceptions, scored_successfully)[source]#

An exception raised when a pipeline errors while scoring any objective in a list of objectives.

Parameters
  • exceptions (dict) – 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.

  • scored_successfully (dict) – A dictionary mapping an objective name (str) to a score value. All of the objectives that did not error will be stored here.

class evalml.exceptions.exceptions.ValidationErrorCode[source]#

Enum identifying the type of error encountered in holdout validation.

Attributes

INVALID_HOLDOUT_GAP_SEPARATION

invalid_holdout_gap_separation

INVALID_HOLDOUT_LENGTH

invalid_holdout_length

Methods

name

The name of the Enum member.

value

The value of the Enum member.

name(self)#

The name of the Enum member.

value(self)#

The value of the Enum member.