GFDL 0.1.0

GFDL 0.1.0 Release Notes

Gradient free deep learning (GFDL) 0.1.0 is the culmination of 6
months of hard work. This first release contains three new estimators.
Our development attention will now shift to bug-fix releases on the
0.1.x branch, and on adding new features on the main branch.

This release requires Python 3.12-3.14.

Highlights of this release

• The new GFDLClassifier is an estimator offering single and
  multi-layer random vector functional link (RVFL) and extreme learning
  machine (ELM) gradient-free neural networks. A regression equivalent,
  GFDLRegressor, has also been added.
• The new EnsembleGFDLClassifier offers a connected ensemble
  of estimators for multi-layer RVFLs that contribute to model output via
  soft or hard voting.

New features

gfdl.model improvements

• Three new estimators that include single and multi layer extreme learning
  machines (ELMs) and random vector functional link (RVFL) networks:
  GFDLClassifier, GFDLRegressor, and EnsembleGFDLClassifier.

Authors

• Name (commits)
• Navamita Ray (138)
• Tyler Reddy (149) +
• Emma Viani (66) +

A total of 3 people contributed to this release.
People with a "+" by their names contributed a patch for the first time.
This list of names is automatically generated, and may not be fully complete.