scientific-active-learning
CommunityOptimize model accuracy with active learning.
Data & Analytics#machine-learning#active-learning#model-improvement#uncertainty-sampling#query-by-committee#data-pool
Authornahisaho
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Designs, implements, and evaluates active-learning pipelines to minimize labeling costs while maximizing model accuracy.
Core Features & Use Cases
- Uncertainty sampling for informative labeling
- Query-by-Committee and other disagreement-based strategies
- Batch active learning and pool/stream sampling
- Stopping criteria and convergence monitoring
Quick Start
Run the active-learning loop with your labeled data, unlabeled pool, and test set to iteratively improve a classifier.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 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: scientific-active-learning Download link: https://github.com/nahisaho/satori/archive/main.zip#scientific-active-learning Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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