bayesian-optimization-tools
OfficialOptimize experiments with AI suggestions.
Education & Research#optimization#experiment design#bayesian optimization#parameter tuning#scientific research#gaussian process
AuthorDrugClaw
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill automates the process of suggesting the next best experiment or parameter set to run, especially when evaluations are costly and the search space is continuous.
Core Features & Use Cases
- Experiment Suggestion: Recommends the next experimental conditions to maximize or minimize an objective.
- Parameter Tuning: Optimizes reaction or assay conditions within defined bounds.
- Closed-Loop Optimization: Facilitates iterative improvement of models or simulations.
Quick Start
Use the bayesian-optimization-tools skill to suggest the next experiment conditions by running the python script with your input data and desired parameters.
Dependency Matrix
Required Modules
numpysklearn
Components
scriptsreferencesassets
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: bayesian-optimization-tools Download link: https://github.com/DrugClaw/DrugClaw/archive/main.zip#bayesian-optimization-tools Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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