l0
OfficialSparsify ML models, speed up data analysis.
Data & Analytics#data science#machine learning#pytorch#sampling#l0 regularization#survey data#sparsity
AuthorPolicyEngine
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill helps PolicyEngine create more efficient survey datasets by intelligently selecting which households to include in calculations. This leads to faster population impact calculations and smaller dataset sizes while maintaining accuracy.
Core Features & Use Cases
- Intelligent Sampling: Provides sampling gates for household selection, feature selection, and sparse weighting.
- Performance Optimization: Reduces the number of households needed for simulation, speeding up PolicyEngine calculations.
- Use Case: Select 1,000 representative households from a 10,000-household survey to accelerate microsimulation without compromising accuracy.
Quick Start
Use the l0 skill to select 1,000 representative households from your data DataFrame.
Dependency Matrix
Required Modules
l0-python
Components
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: l0 Download link: https://github.com/PolicyEngine/policyengine-claude/archive/main.zip#l0 Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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