CLASSIFY THE NUMBER BASED ON THE CONDITIONS SPECIFIED. USEFUL FOR CLASSIFYING NUMERIC VALUE SUCH AS HIC, INTO GOOD, BAD, UGLY.¶
Classifies a numeric scalar value into a named category (e.g., Good, Bad, Ugly) based on a set of user-defined threshold conditions. Useful for bucketing engineering KPIs such as HIC, neck force, or any response metric into Pass/Fail or multi-tier rating bands.
When to use¶
Classification: process.
Tagged: classification, condition, hic, kpi, numeric, pass_fail, rating, scalar.
Inputs¶
| Label | ID | Type | Default | Required | Description |
|---|---|---|---|---|---|
| Response to classify | responsetoclassify | scalar | — | The numeric scalar value to be classified (e.g., a HIC score, peak force, or any KPI output); leave unconnected only if testing condition logic in isolation. | |
| value label | valuelabel | string | Unknown | Fallback label string returned when none of the defined conditions are satisfied; defaults to ‘Unknown’ and should be overridden with a domain-meaningful string such as ‘No Data’ or ‘Undefined’. | |
| Condition | condition | labelcondition | — | One or more label-condition rule(s) that map numeric ranges or comparison expressions to output category names (e.g., value < 700 → ‘Good’); repeatable to define multi-tier classifications. |
Outputs¶
| Label | ID | Type | Description |
|---|---|---|---|
| classify_number_output_1 | classify_number_output_1 | scalar | The string label of the first matching condition category assigned to the input scalar (e.g., ‘Good’, ‘Bad’, ‘Ugly’), or the fallback value label if no condition is satisfied. |
Disciplines¶
- ai_ml.supervised.classification
- cae.postprocessing.response
- data.statistics
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