Description
Label a supplied group's training, validation, test or excluded assignment.
Data workflows require explicit training scope, feature/label availability, missingness codes, group assignments and evaluation direction. Supplied training statistics are not proof that preprocessing avoided leakage. A local target-encoding term or retransformed prediction depends on assumptions that must be checked in the complete model and validation design.
Label a supplied group's training, validation, test or excluded assignment.
When to use this tool
Use Dataset Split Single Group Tag when you already have groupId, splitLabel and need to label a supplied group's training, validation, test or excluded assignment.
How to use the tool and how it works
- Enter groupId, splitLabel. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read tag. Use the output convention below.
Require groupId nonempty and one listed splitLabel; append the label.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| groupId | Group Id | Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 8192. |
| splitLabel | Split Label | Required. Text; one of "train", "validation", "test", "excluded"; maximum UTF-16 length 8192. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| tag | Tag | Required. Text; maximum UTF-16 length 8192. |
{
"input": {
"groupId": "G17",
"splitLabel": "test"
},
"output": {
"tag": "G17 [test]"
}
}Limitations and assumptions
- No split is created or validated. Group independence, temporal order, leakage prevention and actual membership are not established.
- Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.
Alternative or Complementary methods
Review the full data lineage, preprocessing fit, split design and evaluation procedure for model conclusions. Estimate required statistics only within the intended training folds and verify actual availability; local supplied-value transformations cannot establish those properties by themselves.
References
Similar or alternative tools
- Train Test Single Identifier Collision
Check whether one supplied identifier appears in both training and test lists.
- Dataset Stratum Sampling Fraction
Calculate a supplied stratum's sampling fraction and remainder.