How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
This is a Python scientific computing library for finding the global maximum of expensive black-box functions. It operates as a global optimization framework that identifies optimal input parameters within defined bounds to maximize a target output. The library utilizes Gaussian process regression to predict function values and uncertainty, guiding the search for optimal parameters. It employs a surrogate-model optimization approach to approximate high-cost objective functions, reducing the total number of required evaluations. The system manages the trade-off between exploration and exploit
Hyperopt is a Python library for hyperparameter optimization designed to minimize scalar-valued objective functions. It operates as a stochastic search space engine that finds optimal input parameters by searching through real-valued, discrete, and conditional spaces. The framework distinguishes itself through its support for complex search space configurations, allowing for conditional parameter hierarchies where specific hyperparameters are sampled only if their parent parameters meet certain criteria. It is built as an asynchronous optimization framework, decoupling the generation of searc
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
The main features of automl/smac3 are: Automated Machine Learning, Optimization.
Open-source alternatives to automl/smac3 include: hyperopt/hyperopt-sklearn — Hyper-parameter optimization for sklearn. hips/spearmint — Spearmint Bayesian optimization codebase. claesenm/optunity — optimization routines for hyperparameter tuning. hyperopt/hyperopt — Hyperopt is a Python library for hyperparameter optimization designed to minimize scalar-valued objective functions.… fmfn/bayesianoptimization — This is a Python scientific computing library for finding the global maximum of expensive black-box functions. It… optuna/optuna — Optuna is a Python-based hyperparameter optimization framework designed to automate the search for optimal machine…
