Python-ELM-master.zip_ELM极限学习机_python ELM_python elm回归_多分类

Python-ELM ========== Extreme Learning Machine implementation in Python Version 1.0 This is an implementation of the Extreme Learning Machine in python, based on the scikit-learn machine learning library. Distance and dot product based hidden layers are provided via the RBFRandomHiddenLayer and SimpleRandomHiddenLayer classes respectively. The SimpleRandomHiddenLayer provides the following activation functions: tanh, sine, tribas, sigmoid, hardlim The RBFRandomHiddenLayer provides the following activation functions: gaussian, multiquadric and polyharmonic spline ('poly_spline') In addition, each random hidden layer class can take a callable user provided transfer function. See the docstrings and the example ipython notebook for details. There's a little demo in plot_elm_comparison.py (based on scikit-learn's plot_classifier_comparison). Requires that scikit-learn be installed, along with its usual prerequisites, and ipython to use elm_notebook.py (though it can be tweaked to run without it). This is a work in progress, it may be restructured as time goes by. - David C Lambert March, 2013 [dcl -at- panix -dot- com]