Proxy Labels

Proxy labels in machine learning are surrogate labels used when actual labels are not available or hard to obtain. They are derived from available data and are used as stand-ins for the true labels during the training of a model.

Application of Proxy Labels

Proxy labels are particularly useful in semi-supervised learning and in situations where labeling data is expensive or impractical. While they may not perfectly represent the true labels, they can still provide valuable information for training models.

Lakera LLM Security Playbook
Learn how to protect against the most common LLM vulnerabilities

Download this guide to delve into the most common LLM security risks and ways to mitigate them.

Related terms
untouchable mode.
Get started for free.

Lakera Guard protects your LLM applications from cybersecurity risks with a single line of code. Get started in minutes. Become stronger every day.

Join our Slack Community.

Several people are typing about AI/ML security. 
Come join us and 1000+ others in a chat that’s thoroughly SFW.