Extreme Learning Machine regressor/classifer compatible with scikit-learn
Project description
Scikit-ELM
scikit-elm is a scikit-learn compatible Extreme Learning Machine (ELM) regressor/classifier.
It features very high degree of model flexibility: dynamically added classes, partial_fit without performance penalties, wide data format compatibility, optimization and parameter selection without full re-training.
Big Data and out-of-core learning support through dask-powered backend. GPU acceleration support with NVidia hardware, and on macOS through plaidml.
Toolbox is in active development, initial release soon.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
scikit-elm-0.21a0.tar.gz
(21.6 kB
view hashes)
Built Distribution
Close
Hashes for scikit_elm-0.21a0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2306800aa2b30eaa4f4d25f4c1138135dffaca92598853e1149da229b83f9a97 |
|
MD5 | 42d0e52fb85e3fa5128baea29cc6c482 |
|
BLAKE2b-256 | 8c3985bd3c51826576012176e8376dd60d8c2e860e892f5e85b80c948fb35071 |