Variance
In machine learning, variance refers to the extent to which a model's predictions vary for a given data point. High variance often indicates an overly complex model that models noise in the training data, leading to overfitting.
Variance in Model Performance
Variance is one part of the bias-variance tradeoff, a fundamental concept in machine learning. A model with high variance pays too much attention to the training data and does not generalize well to new data. The goal is to balance bias (underfitting) and variance (overfitting) for optimal model performance.
Download this guide to delve into the most common LLM security risks and ways to mitigate them.
untouchable mode.
Lakera Guard protects your LLM applications from cybersecurity risks with a single line of code. Get started in minutes. Become stronger every day.
Several people are typing about AI/ML security. 
Come join us and 1000+ others in a chat that’s thoroughly SFW.