Problem Types¶

The supported types of machine learning problems.

Submodules¶

Package Contents¶

Classes Summary¶

ProblemTypes

Enum defining the supported types of machine learning problems.

Functions¶

`detect_problem_type`	Determine the type of problem is being solved based on the targets (binary vs multiclass classification, regression). Ignores missing and null data.
`handle_problem_types`	Handles problem_type by either returning the ProblemTypes or converting from a str.
`is_binary`	Determines if the provided problem_type is a binary classification problem type.
`is_classification`	Determines if the provided problem_type is a classification problem type.
`is_multiclass`	Determines if the provided problem_type is a multiclass classification problem type.
`is_regression`	Determines if the provided problem_type is a regression problem type.
`is_time_series`	Determines if the provided problem_type is a time series problem type.

Contents¶

evalml.problem_types.detect_problem_type(y)[source]¶

Determine the type of problem is being solved based on the targets (binary vs multiclass classification, regression). Ignores missing and null data.

Parameters: y (pd.Series) – The target labels to predict.
Returns: ProblemType Enum
Return type: ProblemType

Example

>>> y = pd.Series([0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1])
>>> problem_type = detect_problem_type(y)
>>> assert problem_type == ProblemTypes.BINARY

Raises: ValueError – If the input has less than two classes.

evalml.problem_types.handle_problem_types(problem_type)[source]¶

Handles problem_type by either returning the ProblemTypes or converting from a str.

Parameters

problem_type (str or ProblemTypes) – Problem type that needs to be handled.

Returns

ProblemTypes enum

Raises

KeyError – If input is not a valid ProblemTypes enum value.
ValueError – If input is not a string or ProblemTypes object.

evalml.problem_types.is_binary(problem_type)[source]¶

Determines if the provided problem_type is a binary classification problem type.

Parameters: problem_type (str or ProblemTypes) – type of supervised learning problem. See evalml.problem_types.ProblemType.all_problem_types for a full list.
Returns: Whether or not the provided problem_type is a binary classification problem type.
Return type: bool

evalml.problem_types.is_classification(problem_type)[source]¶

Determines if the provided problem_type is a classification problem type.

Parameters: problem_type (str or ProblemTypes) – type of supervised learning problem. See evalml.problem_types.ProblemType.all_problem_types for a full list.
Returns: Whether or not the provided problem_type is a classification problem type.
Return type: bool

evalml.problem_types.is_multiclass(problem_type)[source]¶

Determines if the provided problem_type is a multiclass classification problem type.

Parameters: problem_type (str or ProblemTypes) – type of supervised learning problem. See evalml.problem_types.ProblemType.all_problem_types for a full list.
Returns: Whether or not the provided problem_type is a multiclass classification problem type.
Return type: bool

evalml.problem_types.is_regression(problem_type)[source]¶

Determines if the provided problem_type is a regression problem type.

Parameters: problem_type (str or ProblemTypes) – type of supervised learning problem. See evalml.problem_types.ProblemType.all_problem_types for a full list.
Returns: Whether or not the provided problem_type is a regression problem type.
Return type: bool

evalml.problem_types.is_time_series(problem_type)[source]¶

Determines if the provided problem_type is a time series problem type.

Parameters: problem_type (str or ProblemTypes) – type of supervised learning problem. See evalml.problem_types.ProblemType.all_problem_types for a full list.
Returns: Whether or not the provided problem_type is a time series problem type.
Return type: bool

class evalml.problem_types.ProblemTypes[source]¶

Enum defining the supported types of machine learning problems.

Attributes

BINARY	Binary classification problem.
MULTICLASS	Multiclass classification problem.
REGRESSION	Regression problem.
TIME_SERIES_BINARY	Time series binary classification problem.
TIME_SERIES_MULTICLASS	Time series multiclass classification problem.
TIME_SERIES_REGRESSION	Time series regression problem.

Methods

`all_problem_types`	Get a list of all defined problem types.
`name`	The name of the Enum member.
`value`	The value of the Enum member.

all_problem_types(cls)¶

Get a list of all defined problem types.

Returns: List of all defined problem types.
Return type: list(ProblemTypes)

name(self)¶: The name of the Enum member.

value(self)¶: The value of the Enum member.

utils

problem_types