[scikit-learn] Pipegraph is on its way!

[Andrew Howe]

Very cool!  Thanks for all the great work.

Andrew

<~~~~~~~~~~~~~~~~~~~~~~~~~~~>
J. Andrew Howe, PhD
www.andrewhowe.com
http://orcid.org/0000-0002-3553-1990
http://www.linkedin.com/in/ahowe42
https://www.researchgate.net/profile/John_Howe12/
I live to learn, so I can learn to live. - me
<~~~~~~~~~~~~~~~~~~~~~~~~~~~>

On Wed, Feb 7, 2018 at 6:49 PM, Manuel Castejón Limas <
manuel.castejon at gmail.com> wrote:

> Dear all,
>
> after some playing with the concept we have developed a module for
> implementing the functionality of Pipeline in more general contexts as
> first introduced in a former thread ( https://mail.python.org/piperm
> ail/scikit-learn/2018-January/002158.html )
>
> In order to expand the possibilities of Pipeline for non linearly
> sequential workflows a graph like structure has been deployed while keeping
> as much as possible the already known syntax we all love and honor:
>
> X = pd.DataFrame(dict(X=[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]))
> y = 2 * X
> sc = MinMaxScaler()
> lm = LinearRegression()
> steps = [('scaler', sc),
>          ('linear_model', lm)]
> connections = {'scaler': dict(X='X'),
>                'linear_model': dict(X=('scaler', 'predict'),
>                                     y='y')}
> pgraph = PipeGraph(steps=steps,
>                    connections=connections,
>                    use_for_fit='all',
>                    use_for_predict='all')
>
> As you can see the biggest difference for the final user is the dictionary
> describing the connections.
>
> Another major contribution for developers wanting to expand scikit learn
> is a collection of adapters for scikit learn models in order to provide
> them a common API irrespectively of whether they originally implemented
> predict, transform or fit_predict as an atomic operation without predict.
> These adapters accept as many positional or keyword parameters in their fit
> predict methods through *pargs and **kwargs.
>
> As general as PipeGraph is, it cannot work under the restrictions imposed
> by GridSearchCV on the input parameters, namely X and y since PipeGraph can
> accept as many input signals as needed. Thus, an adhoc GridSearchCv version
> is also needed and we will provide a basic initial version in a later
> version.
>
> We need to write the documentation and we will propose it as a
> contrib-project in a few days.
>
> Best wishes,
> Manuel Castejón-Limas
>
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