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Model

This section documents the model components of the linear_model module.

model

Defines sklearn.linear_model models interoperability.

This module provides functions to create scikit-learn linear model instances from Nextmv options.

FUNCTION DESCRIPTION
LinearRegression

Creates a scikit-learn LinearRegression model from Nextmv options.

LinearRegression 

LinearRegression(options: Options) -> LinearRegression

Creates a sklearn.linear_model.LinearRegression from the provided options.

You can import the LinearRegression function directly from linear_model:

from nextmv_sklearn.linear_model import LinearRegression

This function takes a Nextmv options object and configures a scikit-learn LinearRegression model with the appropriate parameters. It extracts parameter values from the options object that match the expected parameters for LinearRegression.

PARAMETER DESCRIPTION

options

Options for the LinearRegression. Can include the following parameters:

  • fit_intercept : bool, default=True Whether to calculate the intercept for this model.
  • copy_X : bool, default=True If True, X will be copied; else, it may be overwritten.
  • n_jobs : int, default=None The number of jobs to use for the computation.
  • positive : bool, default=False When set to True, forces the coefficients to be positive.

TYPE: Options

RETURNS DESCRIPTION
LinearRegression

A scikit-learn LinearRegression instance configured with the parameters from the options.

Examples:

>>> from nextmv_sklearn.linear_model.options import LinearRegressionOptions
>>> options = LinearRegressionOptions().to_nextmv()
>>> # Modify options if needed
>>> options.fit_intercept = False
>>> model = LinearRegression(options)
Source code in nextmv-scikit-learn/nextmv_sklearn/linear_model/model.py 
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def LinearRegression(options: nextmv.Options) -> linear_model.LinearRegression:
    """
    Creates a `sklearn.linear_model.LinearRegression` from the provided
    options.

    You can import the `LinearRegression` function directly from `linear_model`:

    ```python
    from nextmv_sklearn.linear_model import LinearRegression
    ```

    This function takes a Nextmv options object and configures a scikit-learn
    LinearRegression model with the appropriate parameters. It extracts
    parameter values from the options object that match the expected parameters
    for LinearRegression.

    Parameters
    ----------
    options : nextmv.Options
        Options for the LinearRegression. Can include the following parameters:

        - fit_intercept : bool, default=True
            Whether to calculate the intercept for this model.
        - copy_X : bool, default=True
            If True, X will be copied; else, it may be overwritten.
        - n_jobs : int, default=None
            The number of jobs to use for the computation.
        - positive : bool, default=False
            When set to True, forces the coefficients to be positive.

    Returns
    -------
    sklearn.linear_model.LinearRegression
        A scikit-learn LinearRegression instance configured with the
        parameters from the options.

    Examples
    --------
    >>> from nextmv_sklearn.linear_model.options import LinearRegressionOptions
    >>> options = LinearRegressionOptions().to_nextmv()
    >>> # Modify options if needed
    >>> options.fit_intercept = False
    >>> model = LinearRegression(options)
    """

    names = {p.name for p in LINEAR_REGRESSION_PARAMETERS}
    opt_dict = {k: v for k, v in options.to_dict().items() if k in names if v is not None}

    return linear_model.LinearRegression(**opt_dict)