Python Extreme Learning Machine (ELM)
Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.
Free software: BSD license
Documentation: https://elm.readthedocs.org.
Features
ELM Kernel
ELM Random Neurons
MLTools
History
0.1.0 (2015-02-03)
First release on PyPI.
0.1.1 (2015-02-10)
Fixed some package issues.
Added Python 2.7 support
Added extra parameter to search_param method.
0.1.2 (2017-09-19)
Fixed a bug when using search_param.
Optunity solver is available when using search_param.
1 maintainer
Metadata
1 maintainer
Release files for elm 0.1.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| elm-0.1.3.tar.gz | 74.2 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| elm-0.1.3-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 93.2 kB
Release files / elm-0.1.3.tar.gz
| Download URL | elm-0.1.3.tar.gz |
|---|---|
| Size | 74.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.12.1 pkginfo/1.4.2 requests/2.20.1 setuptools/40.6.2 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/3.6.6
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Release files / elm-0.1.3-py2.py3-none-any.whl
| Download URL | elm-0.1.3-py2.py3-none-any.whl |
|---|---|
| Size | 19.0 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.12.1 pkginfo/1.4.2 requests/2.20.1 setuptools/40.6.2 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/3.6.6
|
Security for elm 0.1.3
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No provenance found
None of the files in this release were uploaded with provenance metadata.
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