Skip to main content

High-Performance implementation of an Extreme Learning Machine

Project description

High Performance ELM
--------

Extreme Learning Machine (ELM) with model selection and regularizations.

In-memory ELM works, check hpelm/tests folder.
MAGMA acceleration works, check hpelm/acc/setup_gpu.py.


Example usage::

>>> from hpelm import ELM
>>> elm = ELM(X.shape[1], T.shape[1])
>>> elm.add_neurons(20, "sigm")
>>> elm.add_neurons(10, "rbf_l2")
>>> elm.train(X, T, "LOO")
>>> Y = elm.predict(X)

If you use the toolbox, cite our paper that will be published in IEEE Access.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

hpelm-0.6.0.tar.gz (22.8 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page