Principle:Snorkel team Snorkel Labeling Function Analysis

Knowledge Sources	Data Programming: Creating Large Training Sets Quickly Training Complex Models with Multi-Task Weak Supervision
Domains	Weak_Supervision, Data_Quality, Statistics
Last Updated	2026-02-14 20:00 GMT

Overview

A statistical analysis framework for evaluating the quality, coverage, overlap, and conflict patterns of labeling functions before training a label model.

Description

Labeling Function Analysis provides diagnostic statistics about LF behavior on a dataset. Before investing compute in training a label model, practitioners need to understand how their LFs are performing: which ones have high coverage, which ones agree or conflict with each other, and (if gold labels are available) which ones are empirically accurate.

Key metrics include:

• Coverage: Fraction of data points labeled by an LF (non-abstain rate)
• Overlap: Fraction of data points labeled by multiple LFs
• Conflict: Fraction of data points where LFs disagree
• Empirical accuracy: Agreement with gold labels on a development set
• Polarity: The set of distinct labels an LF produces

These diagnostics are essential for iterative LF development: identifying LFs with low coverage, high conflict rates, or poor accuracy guides the refinement process.

Usage

Use this principle after applying labeling functions and before training a label model. Analyze LF quality to identify poorly performing LFs that should be modified or removed. Repeat analysis iteratively as you refine your LF set.

Theoretical Basis

Given label matrix $L\in {\mathbb{\mathbb{Z}}}^{n\times m}$:

Coverage of LF $j$: $\text{coverage}({\lambda }_j)=\frac{|\{i:L_{i,j}\ne -1\}|}{n}$

Overlap rate: $\text{overlap}=\frac{|\{i:|\{j:L_{i,j}\ne -1\}|>1\}|}{n}$

Conflict rate: $\text{conflict}=\frac{|\{i:\mathrm{\exists }j,k\text{ s.t. }{L}_{i,j}\ne L_{i,k},L_{i,j}\ne -1,L_{i,k}\ne -1\}|}{n}$

Empirical accuracy (with gold labels $Y$): $\text{acc}({\lambda }_j)=\frac{|\{i:L_{i,j}=Y_i,L_{i,j}\ne -1\}|}{|\{i:L_{i,j}\ne -1\}|}$

Related Pages

Implemented By

• Implementation:Snorkel_team_Snorkel_LFAnalysis_Summary