Description
Check a label-availability date against a training cutoff under an equality policy.
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.
Check a label-availability date against a training cutoff under an equality policy.
When to use this tool
Use Target Label Availability Date Flag when you already have labelAvailableDate, trainingCutoffDate, cutoffInclusive and need to check a label-availability date against a training cutoff under an equality policy.
How to use the tool and how it works
- Enter labelAvailableDate, trainingCutoffDate, cutoffInclusive. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read availableByCutoff. Inspect availableByCutoff before interpreting the associated values.
Parse real UTC dates; compare availableDate<=cutoff when inclusive, otherwise availableDate<cutoff.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| labelAvailableDate | Label Available Date | Required. Text; maximum UTF-16 length 8192. Real proleptic Gregorian YYYY-MM-DD; four-digit years 0000-9999 accepted. |
| trainingCutoffDate | Training Cutoff Date | Required. Text; maximum UTF-16 length 8192. Real proleptic Gregorian YYYY-MM-DD; four-digit years 0000-9999 accepted. |
| cutoffInclusive | Choose availability-date equality as accepted or rejected; no within-day time is represented. | Required. Boolean. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| availableByCutoff | Available By Cutoff | Required. Boolean. |
{
"input": {
"labelAvailableDate": "2026-10-31",
"trainingCutoffDate": "2026-11-01",
"cutoffInclusive": false
},
"output": {
"availableByCutoff": true
}
}Limitations and assumptions
- Date-level availability is a supplied assertion, not verified information timing. No within-day cutoff, target leakage or valid train/test design is 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
- Event Time Feature Time Order Flag
Compare supplied feature availability with an event time and equality policy.
- Train Test Single Identifier Collision
Check whether one supplied identifier appears in both training and test lists.