scikit_nodes¶
Module: missions.nodes.scikit_nodes
¶
Wrap the algorithms defined in scikit.learn in pySPACE nodes
For details on parameter usage look at the scikit documentation or the wrapped documentation of pySPACE: Scikit Nodes. The parameters given in the node specification are filtered, to check if they are available, and then directly forwarded to the scikit algorithm.
This module is based heavily on the scikit.learn wrapper for the “Modular toolkit for Data Processing” (MDP, version 3.3, http://mdp-toolkit.sourceforge.net/). All credit goes to the MDP authors.
MDP (version 3.3) is distributed under the following BSD license:
This file is part of Modular toolkit for Data Processing (MDP).
All the code in this package is distributed under the following conditions:
Copyright (c) 2003-2012, MDP Developers <mdp-toolkit-devel@lists.sourceforge.net>
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
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* Redistributions in binary form must reproduce the above copyright
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* Neither the name of the Modular toolkit for Data Processing (MDP)
nor the names of its contributors may be used to endorse or promote
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Inheritance diagram for pySPACE.missions.nodes.scikit_nodes
:
Class Summary¶
ScikitException |
Base class for exceptions in nodes wrapping scikit algorithms. |
Function Summary¶
apply_to_scikit_algorithms (current_module, ...) |
Function that traverses a module to find scikit algorithms. |
wrap_scikit_classifier (scikit_class) |
Wrap a sklearn classifier as a BaseNode subclass. |
wrap_scikit_transformer (scikit_class) |
Wrap a sklearn transformer as a pySPACE BaseNode subclass |
wrap_scikit_predictor (scikit_class) |
Wrap a sklearn predictor as an pySPACE BaseNode subclass |
print_public_members (class_) |
Print methods of sklearn algorithm |
wrap_scikit_algorithms (scikit_class, nodes_list) |
Check scikit_class and append new wrapped class to nodes_list |
Class¶
Functions¶
apply_to_scikit_algorithms()
¶
-
pySPACE.missions.nodes.scikit_nodes.
apply_to_scikit_algorithms
(current_module, action, processed_modules=None, processed_classes=None)[source]¶ Function that traverses a module to find scikit algorithms.
‘sklearn’ algorithms are identified by the ‘fit’ ‘predict’, or ‘transform’ methods. The ‘action’ function is applied to each found algorithm.
- action – a function that is called with as
action(class_)
, where class_
is a class that defines the ‘fit’ or ‘predict’ method
- action – a function that is called with as
wrap_scikit_algorithms()
¶
-
pySPACE.missions.nodes.scikit_nodes.
wrap_scikit_algorithms
(scikit_class, nodes_list)[source]¶ Check scikit_class and append new wrapped class to nodes_list
Currently only classifiers subclassing
sklearn.base.ClassifierMixin
and having a fit method were integrated and tested. Algorithms with the transform function are also available. predict nodes will be available soon but require more testing especially of regression in pySPACE.