Randomer Forest (RerF) Python Package
Randomer Forest combines sparse random projections with the random forest algorithm to achieve high accuracy on a variety of datasets.
Documentation for RerF Python module can be found at rerf.neurodata.io.
Install
See install instructions.
Example
See example for basic usage.
Reference
Function references can be found in our docs.
Tests
We use pytest for Python testing.
Run the tests from command line at the root of the repo (RerF/).
python -m pytest
Publish new version
To upload to PyPi see PUBLISH.md
Release files for rerf 2.0.5
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 | Actions |
|---|---|---|---|---|
| rerf-2.0.5.tar.gz | 70.5 kB | Without provenance | Details for rerf-2.0.5.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| rerf-2.0.5-cp37-cp37m-macosx_10_14_x86_64.whl | CPython 3.7 | CPython 3.7 pymalloc | macOS 10.14+ x86-64 | Details for rerf-2.0.5-cp37-cp37m-macosx_10_14_x86_64.whl |
Total release size: 294.2 kB
Release files / rerf-2.0.5.tar.gz
| Download URL | rerf-2.0.5.tar.gz |
|---|---|
| Size | 70.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
020c08223786706ede4cb8cba4ddf622ab10ffbba82b3df5a8618e72b762d6a6
|
|
BLAKE2b-256 checksum How to use checksums |
0e0d491d53324bfef3013d4ddc92de83e02a56dd1642ac317de9a18dbd0769a1
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/3.7.3
|
Release files / rerf-2.0.5-cp37-cp37m-macosx_10_14_x86_64.whl
| Download URL | rerf-2.0.5-cp37-cp37m-macosx_10_14_x86_64.whl |
|---|---|
| Size | 223.7 kB |
| Tags | CPython 3.7 CPython 3.7 pymalloc macOS 10.14+ x86-64 |
|
SHA-256 checksum How to use checksums |
fb16e321f4c9bfd85aec79cc5402ad63bf96c7c1fcdf5db881cfb6c802768efb
|
|
BLAKE2b-256 checksum How to use checksums |
777ae005c6521ed2a5099b7dffbde8a34b9c2f919c223e53d6ad9e89befe8224
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/3.7.3
|
Security for rerf 2.0.5
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
