gemseo.mlearning.clustering.algos.gaussian_mixture_settings module#

Settings of the Gaussian mixture model.

Settings GaussianMixture_Settings(*, transformer=<factory>, parameters=<factory>, var_names=(), n_clusters=5, random_state=0)[source]#

Bases: BaseClustererSettings

The settings of the Gaussian mixture model.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

  • transformer (Mapping[str, Any]) --

    By default it is set to <factory>.

  • parameters (Mapping[str, Any]) --

    By default it is set to <factory>.

  • var_names (Sequence[str]) --

    By default it is set to ().

  • n_clusters (Annotated[int, Gt(gt=0)]) --

    By default it is set to 5.

  • random_state (Annotated[int, Ge(ge=0)] | None) --

    By default it is set to 0.

Return type:

None

model_post_init(context, /)#

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that's what pydantic-core passes when calling it.

Parameters:

  • self (BaseModel) -- The BaseModel instance.

  • context (Any) -- The context.

Return type:

None