#139139th of 206 in ML frameworks and libraries
mlxtend
Python library of scikit-learn extensions for ensembles, feature selection and plotting
- Stars
- 5.2k
- License
- custom license
- Last commit
- Sep 2026
- Last release
- Jun 2026
- Language
- Python
5,105 on 21 Apr 20265,193 on 10 Nov 2026
From GitHub's daily star counts.
Checked on GitHub.
Overview
mlxtend is a Python library that adds data science utilities on top of the scientific Python stack. It provides stacking and voting classifiers, feature selection and extraction, decision-region and confusion-matrix plots, and Apriori-based frequent pattern mining for association rules. It installs from PyPI and works with scikit-learn estimators.
Who it is for: Data scientists using scikit-learn who need ensembles, plots and pattern mining
Strengths
- Covers stacking, voting, feature selection and association rule mining in one package
- Decision-region plotting works with scikit-learn-style classifiers
- Published in JOSS with a DOI, documentation and changelog
- BSD license, stated as commercially usable
Weaknesses
- Classical ML only; no LLM, deep learning or agent features
- Scope is broad and loosely related, with no single focus
- Plotting example uses only two features of the iris data
- Repo license detected as NOASSERTION, while README states BSD
What it needs
- no GPU
- Needs scikit-learn, numpy, matplotlib
- Models: scikit-learn estimators
What changed
From the release notes. No flag means the note does not say so, not that the upgrade is safe.
Also in ML frameworks and libraries
See all 206| Rank | Project | Score |
|---|---|---|
| 1 | transformersPython library defining open models for text, vision, audio and multimodal tasks | 94 out of 100 |
| 2 | ultralyticsPython library and CLI for training and running YOLO vision models | 94 out of 100 |
| 3 | pytorchPython tensor library with GPU support and tape-based autograd | 93 out of 100 |
| #4 | pytorch-image-modelsPyTorch library of image models, pretrained weights and training scripts | 93 out of 100 |
| #5 | supervisionPython toolkit for loading, annotating and counting computer vision detections | 92 out of 100 |