RFMSU

Random Tree and Random Forest classifiers based on Multivariate Symmetrical Uncertainty (MSU).

Features

Random Tree classifier.
Random Tree with MSU.
Random Forest classifier.
Random Forest with MSU.
Local and global discretization.
Parallel training using Joblib.
Out-of-bag evaluation.

Installation

pip install rfmsu

Example

from rfmsu import RandomForestMSU

clf = RandomForestMSU(
    numIterations=100,
    rediscretize_msu_per_node=True,
    n_jobs=-1
)

clf.fit(X_train, y_train)
predictions = clf.predict(X_test)

License

MIT License.

Metadata

Release files for rfmsu 0.1.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for rfmsu 0.1.1
File	Size	Uploaded	Provenance
rfmsu-0.1.1.tar.gz	50.1 kB	Oct 23, 2026	Without provenance	Details

Built distribution (wheel)

Table of built distributions (wheels) for rfmsu 0.1.1
File	Interpreter	ABI	Platform	Reset
rfmsu-0.1.1-py3-none-any.whl 54.8 kB Oct 23, 2026 Without provenance	Python 3	none	any	Details

Total release size: 104.9 kB

Release files / rfmsu-0.1.1.tar.gz

Download URL	rfmsu-0.1.1.tar.gz
Size	50.1 kB
Tags	Source
SHA-256 checksum How to use checksums	`19297350f6ec6297ca988db67046af8500db30014cd7d2d8ff4b6f673e647c8a`
BLAKE2b-256 checksum How to use checksums	`04777c310023ab55169a54f898d7ac69f46425cb786bbbfc09e9ebc92641a71b`
Upload date	Oct 23, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.10.19`

Release files / rfmsu-0.1.1-py3-none-any.whl

Download URL	rfmsu-0.1.1-py3-none-any.whl
Size	54.8 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`3f0997661ef93fde9a2f2ed094b93bfc409a72377b8fb4abaea4f2200fac6214`
BLAKE2b-256 checksum How to use checksums	`c34bb3697aec9610b7c8a63c7072965225dfd02f12b2b814fb52e4d3691daf4d`
Upload date	Oct 23, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.10.19`

Security for rfmsu 0.1.1

Report project as malware

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.