Metadata-Version: 2.4
Name: wlearn
Version: 0.1.0
Summary: Portable ML computation primitives
Author: Anton Zemlyansky
License-Expression: MIT
Project-URL: Homepage, https://github.com/wlearn-org/wlearn
Project-URL: Repository, https://github.com/wlearn-org/wlearn
Keywords: machine-learning,ml,wasm,xgboost,random-forest,portable
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.9
Description-Content-Type: text/markdown
Provides-Extra: xgboost
Requires-Dist: xgboost>=2.0; extra == "xgboost"
Requires-Dist: numpy>=1.22; extra == "xgboost"
Provides-Extra: sklearn
Requires-Dist: scikit-learn>=1.3; extra == "sklearn"
Requires-Dist: numpy>=1.22; extra == "sklearn"
Provides-Extra: liblinear
Requires-Dist: liblinear-official>=2.50; extra == "liblinear"
Requires-Dist: numpy>=1.22; extra == "liblinear"
Provides-Extra: libsvm
Requires-Dist: libsvm-official>=3.30; extra == "libsvm"
Requires-Dist: numpy>=1.22; extra == "libsvm"
Provides-Extra: nanoflann
Requires-Dist: pynanoflann>=0.10; extra == "nanoflann"
Requires-Dist: numpy>=1.22; extra == "nanoflann"
Provides-Extra: ebm
Requires-Dist: numpy>=1.22; extra == "ebm"
Provides-Extra: ebm-fit
Requires-Dist: interpret>=0.6; extra == "ebm-fit"
Requires-Dist: numpy>=1.22; extra == "ebm-fit"
Provides-Extra: xlearn
Requires-Dist: numpy>=1.22; extra == "xlearn"
Provides-Extra: tsetlin
Requires-Dist: numpy>=1.22; extra == "tsetlin"
Provides-Extra: tsetlin-fit
Requires-Dist: tmu>=0.7; extra == "tsetlin-fit"
Requires-Dist: numpy>=1.22; extra == "tsetlin-fit"
Provides-Extra: all
Requires-Dist: xgboost>=2.0; extra == "all"
Requires-Dist: scikit-learn>=1.3; extra == "all"
Requires-Dist: liblinear-official>=2.50; extra == "all"
Requires-Dist: libsvm-official>=3.30; extra == "all"
Requires-Dist: pynanoflann>=0.10; extra == "all"
Requires-Dist: interpret>=0.6; extra == "all"
Requires-Dist: tmu>=0.7; extra == "all"
Requires-Dist: numpy>=1.22; extra == "all"
Provides-Extra: test
Requires-Dist: pytest>=7.0; extra == "test"

# wlearn

Portable ML computation primitives -- classical ML methods compiled from C/C++ with WASM-first JavaScript and native-first Python bindings.

This is a placeholder package. See [github.com/wlearn-org](https://github.com/wlearn-org) for details.
