Cookie Consent
Hi, this website uses essential cookies to ensure its proper operation and tracking cookies to understand how you interact with it. The latter will be set only after consent.
Read our Privacy Policy


Underfitting occurs in machine learning when a model is too simple to capture the underlying patterns in the data. This often happens when the model does not have enough parameters or complexity to learn from the data effectively.

How Underfitting Manifests

A model that underfits usually has poor performance on both training and validation datasets. This can be due to reasons like insufficient training time, overly simple model architecture, or lack of relevant features in the data. Improving the model complexity or feature engineering often helps in addressing underfitting.

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.