Factual package intelligence from PyPI

bayesian-gp-cvloss 0.3.1 package intelligence

A Python package for Gaussian Process Regression with hyperparameter optimization using Hyperopt and cross-validation, focusing on optimizing cross-validated loss.

pip install bayesian-gp-cvloss

Current version
0.3.1
Python requirement
>=3.8
License
MIT
Distribution type
Pure Python wheel
Release files
2 (1 wheels, 1 source)
Download size
47.7 KiB
Release history
10 releases with files
Median release cadence
0 days

bayesian-gp-cvloss dependencies

PyPI declares 5 unique dependency rules for this release. Environment markers are shown when supplied by the project.

  1. gpflow >=2.0.0
  2. hyperopt >=0.2.0
  3. scikit-learn >=0.23.0
  4. pandas >=1.0.0
  5. numpy >=1.18.0

Compatibility and release files

bayesian-gp-cvloss publishes 1 wheel and 1 source archive for version 0.3.1. Wheel platform tags: any.

Declared Python classifiers: 3.10, 3.8, 3.9.

Release activity and sources

PyPI lists 10 releases with files. The first dated release is ; 10 releases fall within the 365 days preceding the latest dated release. The current release files were uploaded on . The preceding dated release was .