Description
Compare supplied feature availability with an event time and 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.
Compare supplied feature availability with an event time and equality policy.
When to use this tool
Use Event Time Feature Time Order Flag when you already have featureAvailableTime, eventTime, allowEquality and need to compare supplied feature availability with an event time and equality policy.
How to use the tool and how it works
- Enter featureAvailableTime, eventTime, allowEquality. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read availableBeforeEvent, lag. Inspect availableBeforeEvent before interpreting the associated values.
Return eventTime-featureAvailableTime as lag; availableBeforeEvent requires earlier availability or equality with allowEquality=true.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| featureAvailableTime | Feature Available Time | Required. Finite number. |
| eventTime | Event Time | Required. Finite number. |
| allowEquality | Allow Equality | Required. Boolean. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| availableBeforeEvent | Available Before Event | Required. Boolean. |
| lag | Event-feature availability time; positive means available earlier under the supplied clocks. | Required. Finite number. |
{
"input": {
"featureAvailableTime": 90,
"eventTime": 100,
"allowEquality": false
},
"output": {
"availableBeforeEvent": true,
"lag": 10
}
}Limitations and assumptions
- A positive lag means availability before the event. No information timestamps, ingestion delay, label leakage or complete evaluation design is verified.
- 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.
- Numeric calculations use binary floating point unless exact decimal-integer arithmetic is explicitly stated. No hidden measurement tolerance or decimal rounding is added; nonfinite or out-of-contract results are rejected. Numeric signed-zero results are exported as zero.
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
- Target Label Availability Date Flag
Check a label-availability date against a training cutoff under an equality policy.
- Feature Timestamp Latency Budget Gap
Measure a supplied latency budget's signed margin.