scikit-lr
scikit-lr is a Python module integrating Machine Learning algorithms for Label Ranking problems and distributed under MIT license.
Installation
Dependencies
scikit-lr requires:
* Python>=3.6
* Numpy>=1.15.2
* SciPy>=1.1.0
Linux or Mac OS X operating systems. Windows is not currently supported.
User installation
The easiest way to install scikit-lr is using pip package:
pip install -U scikit-lr
Development
Feel free to contribute to the package, but be sure that the standards are followed.
Source code
The latest sources can be obtained with the command:
git clone https://github.com/alfaro96/scikit-lr.git
Setting up a development environment
To setup the development environment, it is strongly recommended to use docker tools (see https://github.com/alfaro96/docker-scikit-lr for details).
Alternatively, one can use Python virtual environments (see https://docs.python.org/3/library/venv.html for details).
Testing
After installation the test suite can be executed from outside the source directory, with (you will need to have pytest>=4.6.4 installed):
pytest sklr
Authors
* Alfaro Jiménez, Juan Carlos
* Aledo Sánchez, Juan Ángel
* Gámez Martín, José Antonio
License
This project is licensed under the MIT License - see the LICENSE file for details.
1 maintainer
Release files for scikit-lr 0.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
| File | Reset | |||
|---|---|---|---|---|
| scikit_lr-0.2.0-cp37-cp37m-manylinux1_x86_64.whl | CPython 3.7 | CPython 3.7 pymalloc | Linux glibc 2.5+ x86-64 | Details |
| scikit_lr-0.2.0-cp37-cp37m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl | CPython 3.7 | CPython 3.7 pymalloc | macOS 10.6+ Intel (x86-64, i386), macOS 10.10+ Intel (x86-64, i386), macOS 10.9+ Intel (x86-64, i386), macOS 10.10+ x86-64, macOS 10.9+ x86-64 | Details |
| scikit_lr-0.2.0-cp36-cp36m-manylinux1_x86_64.whl | CPython 3.6 | CPython 3.6 pymalloc | Linux glibc 2.5+ x86-64 | Details |
| scikit_lr-0.2.0-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl | CPython 3.6 | CPython 3.6 pymalloc | macOS 10.6+ Intel (x86-64, i386), macOS 10.10+ x86-64, macOS 10.9+ Intel (x86-64, i386), macOS 10.9+ x86-64, macOS 10.10+ Intel (x86-64, i386) | Details |
Total release size: 40.4 MB
Release files / scikit_lr-0.2.0-cp37-cp37m-manylinux1_x86_64.whl
| Download URL | scikit_lr-0.2.0-cp37-cp37m-manylinux1_x86_64.whl |
|---|---|
| Size | 9.7 MB |
| Tags | CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.5+ x86-64 |
|
SHA-256 checksum How to use checksums |
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|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.5.6
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Release files / scikit_lr-0.2.0-cp37-cp37m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
| Download URL | scikit_lr-0.2.0-cp37-cp37m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl |
|---|---|
| Size | 10.5 MB |
| Tags | CPython 3.7 CPython 3.7 pymalloc macOS 10.10+ Intel (x86-64, i386) macOS 10.10+ x86-64 macOS 10.6+ Intel (x86-64, i386) macOS 10.9+ Intel (x86-64, i386) macOS 10.9+ x86-64 |
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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/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.7.1
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Release files / scikit_lr-0.2.0-cp36-cp36m-manylinux1_x86_64.whl
| Download URL | scikit_lr-0.2.0-cp36-cp36m-manylinux1_x86_64.whl |
|---|---|
| Size | 9.7 MB |
| Tags | CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.5+ x86-64 |
|
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/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.5.6
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Release files / scikit_lr-0.2.0-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
| Download URL | scikit_lr-0.2.0-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl |
|---|---|
| Size | 10.5 MB |
| Tags | CPython 3.6 CPython 3.6 pymalloc macOS 10.10+ Intel (x86-64, i386) macOS 10.10+ x86-64 macOS 10.6+ Intel (x86-64, i386) macOS 10.9+ Intel (x86-64, i386) macOS 10.9+ x86-64 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.2 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.6.7
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