/bopt

Bayesian Optimization using Gaussian Processes + web interface with result visualizations

Primary LanguagePythonMIT LicenseMIT

Bayesian Optimization of HyperParameters - bopt Build Status Maintainability Test Coverage PyPi version Python Version

Available commands:

# Create a new experiment.
bopt init -C META_DIR

# Start tuning hyperparameters.
bopt run -C META_DIR

# Get an overview status of an experiment.
bopt exp -C META_DIR

# Start web visualizations of the results.
bopt web -C META_DIR

Installation

pip install bopt