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Number of nodes

This file is part of the TPOT library.

The current version of TPOT was developed at Cedars-Sinai by: - Pedro Henrique Ribeiro (https://github.com/perib, https://www.linkedin.com/in/pedro-ribeiro/) - Anil Saini (anil.saini@cshs.org) - Jose Hernandez (jgh9094@gmail.com) - Jay Moran (jay.moran@cshs.org) - Nicholas Matsumoto (nicholas.matsumoto@cshs.org) - Hyunjun Choi (hyunjun.choi@cshs.org) - Miguel E. Hernandez (miguel.e.hernandez@cshs.org) - Jason Moore (moorejh28@gmail.com)

The original version of TPOT was primarily developed at the University of Pennsylvania by: - Randal S. Olson (rso@randalolson.com) - Weixuan Fu (weixuanf@upenn.edu) - Daniel Angell (dpa34@drexel.edu) - Jason Moore (moorejh28@gmail.com) - and many more generous open-source contributors

TPOT is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

TPOT is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details.

You should have received a copy of the GNU Lesser General Public License along with TPOT. If not, see http://www.gnu.org/licenses/.

number_of_nodes_objective(est)

Calculates the number of leaves (input nodes) in an sklearn pipeline

Parameters:

Name Type Description Default
est

The pipeline to compute the number of nodes from.

 required
Source code in tpot2/objectives/number_of_nodes.py 
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def number_of_nodes_objective(est):
    """
    Calculates the number of leaves (input nodes) in an sklearn pipeline

    Parameters
    ----------
    est: GraphPipeline | Pipeline | FeatureUnion | BaseEstimator
        The pipeline to compute the number of nodes from.
    """

    if isinstance(est, GraphPipeline):
        return sum(number_of_nodes_objective(est.graph.nodes[node]["instance"]) for node in est.graph.nodes)
    if isinstance(est, Pipeline):
        return sum(number_of_nodes_objective(estimator) for _,estimator in est.steps)
    if isinstance(est, sklearn.pipeline.FeatureUnion):
        return sum(number_of_nodes_objective(estimator) for _,estimator in est.transformer_list)

    return 1