Test set in machine learning is a subset of a dataset used to assess the performance of a model after training. The test set is separate from the training dataset and is not used during the model training process.
Purpose of a Test Set
The test set provides an unbiased evaluation of a model, reflecting its ability to generalize to new, unseen data. For example, in a classification task, the accuracy of the model on the test set indicates how well it can classify new instances.
Download this guide to delve into the most common LLM security risks and ways to mitigate them.
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.