skdownscale.pointwise_models.PiecewiseLinearRegression

class skdownscale.pointwise_models.PiecewiseLinearRegression(n_segments=7, fit_option='auto', pwlf_kwargs=None)[source]

Bases: RegressorMixin, BaseEstimator

Piecewise Linear Regression

Parameters:

  • n_segments (int, default 7) – The desired number of line segments.

  • fit_option ({"auto", "fast", or "arrm"}, default 'auto') – The method to use for fitting the piecewise linear regression.

  • pwlf_kwargs (dict, default None) – Additional keyword arguments to pass to the PiecewiseLinFit init method.

TODO

See also

TODO

__init__(n_segments=7, fit_option='auto', pwlf_kwargs=None)[source]

Methods

__init__([n_segments, fit_option, pwlf_kwargs])

fit(X, y, **kwargs)

get_metadata_routing()

Get metadata routing of this object.

get_params([deep])

Get parameters for this estimator.

predict(X)

score(X, y[, sample_weight])

Return coefficient of determination on test data.

set_params(**params)

Set the parameters of this estimator.

set_score_request(*[, sample_weight])

Configure whether metadata should be requested to be passed to the score method.
set_score_request(*, sample_weight='$UNCHANGED$')

Configure whether metadata should be requested to be passed to the score method.

Note that this method is only relevant when this estimator is used as a sub-estimator within a meta-estimator and metadata routing is enabled with enable_metadata_routing=True (see sklearn.set_config()). Please check the User Guide on how the routing mechanism works.

The options for each parameter are:

  • True: metadata is requested, and passed to score if provided. The request is ignored if metadata is not provided.

  • False: metadata is not requested and the meta-estimator will not pass it to score.

  • None: metadata is not requested, and the meta-estimator will raise an error if the user provides it.

  • str: metadata should be passed to the meta-estimator with this given alias instead of the original name.

The default (sklearn.utils.metadata_routing.UNCHANGED) retains the existing request. This allows you to change the request for some parameters and not others.

Added in version 1.3.

Parameters:

sample_weight (str, True, False, or None, default=sklearn.utils.metadata_routing.UNCHANGED) – Metadata routing for sample_weight parameter in score.

Returns:

self (object) – The updated object.