.. _`Polynomial Features`:

.. _`org.sysess.sympathy.machinelearning.polynomial_features`:

Polynomial Features
~~~~~~~~~~~~~~~~~~~

.. image:: polynomial.svg
   :width: 48


Generate a new feature matrix consisting of all polynomial combinations of the features with less than a given degree

*Configuration*:


  - *degree*

    The degree of the polynomial features. Default = 2.


  - *interaction_only*

    If true, only interaction features are produced: features that are
    products of at most ``degree`` *distinct* input features (so not
    ``x ** 2``, ``x * x ** 3``, etc.).


  - *include_bias*

    If True (default), then include a bias column, the feature in which
    all polynomial powers are zero (i.e. a column of ones - acts as an
    intercept term in a linear model).




*Attributes*:


  - *n_input_features_*

    The total number of input features.


  - *n_output_features_*

    The total number of polynomial output features. The number of output
    features is computed by iterating over all suitably sized combinations
    of input features.


  - *powers_*

    powers_[i, j] is the exponent of the jth input in the ith output.




*Input ports*:


*Output ports*:
    **model** : model
        Model



**degree** (degree)
    The degree of the polynomial features. Default = 2.
**interaction_only** (interaction_only)
    If true, only interaction features are produced: features that are
    products of at most ``degree`` *distinct* input features (so not
    ``x ** 2``, ``x * x ** 3``, etc.).
**include_bias** (include_bias)
    If True (default), then include a bias column, the feature in which
    all polynomial powers are zero (i.e. a column of ones - acts as an
    intercept term in a linear model).

.. automodule:: node_preprocessing

.. class:: PolynomialFeatures