In Arize Phoenix, splits let you categorize your dataset into distinct subsets—such as train, validation, or test—enabling structured workflows for experiments and evaluations. This capability offers more flexibility in how you organize, filter, and compare your data across different stages or experimental conditions. You can query dataset examples by splits, allowing you to focus experiments on specific subsets of your dataset. More on Splits:Documentation Index
Fetch the complete documentation index at: https://arizeai-433a7140-mikeldking-12899-providers-and-secrets.mintlify.app/llms.txt
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Splits Documentation
GitHub
GitHub