Unsupervised learning#
This module contains the base class for the unsupervised machine learning algorithms.
The unsupervised
module implements the concept of
unsupervised machine learning models, where the data has no notion of input or output.
This concept is implemented through the BaseMLUnsupervisedAlgo
class, which
inherits from the BaseMLAlgo
class.
- class BaseMLUnsupervisedAlgo(data, settings_model=None, **settings)[source]
Unsupervised machine learning algorithm.
Inheriting classes shall overload the
BaseMLUnsupervisedAlgo._fit()
method.- Parameters:
data (Dataset) -- The learning dataset.
settings_model (BaseMLAlgoSettings | None) -- The machine learning algorithm settings as a Pydantic model. If
None
, use**settings
.**settings (Any) -- The machine learning algorithm settings. These arguments are ignored when
settings_model
is notNone
.
- Raises:
ValueError -- When both the variable and the group it belongs to have a transformer.
- Settings
alias of
BaseMLUnsupervisedAlgoSettings
- SHORT_ALGO_NAME: ClassVar[str] = 'BaseMLUnsupervisedAlgo'
The short name of the machine learning algorithm, often an acronym.
Typically used for composite names, e.g.
f"{algo.SHORT_ALGO_NAME}_{dataset.name}"
orf"{algo.SHORT_ALGO_NAME}_{discipline.name}"
.