Description
Return distinct label cardinality and capacity slack.
Feature transformations depend on training-derived parameters, category vocabularies and explicit missing-value conventions. A local formula or token rule does not ensure that fitting, application and validation avoid data leakage.
Return distinct label cardinality and capacity slack.
When to use this tool
Use Label Encoding Cardinality Slack when checking one supplied feature-transform or encoding component.
How to use the tool and how it works
- Enter labels, capacity. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read cardinality, slack. Use the output convention below.
Return distinct label cardinality and capacity slack. Require nonnegative whole capacity; cardinality counts exact unique strings and slack = capacity-cardinality.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| labels | Labels | Required. Array of text; maximum UTF-16 length 8192; maximum items 256. |
| capacity | Capacity | Required. Safe integer; minimum 0. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| cardinality | Cardinality | Required. Safe integer. |
| slack | Slack | Required. Safe integer. |
{
"input": {
"labels": [
"a",
"b",
"a"
],
"capacity": 4
},
"output": {
"cardinality": 2,
"slack": 2
}
}Limitations and assumptions
- Negative slack is retained; no labels are encoded and unknown-level policy is not inferred.
- 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
Use a correctly fitted preprocessing pipeline and suitable validation design for complete data transformation and model assessment.
References
Similar or alternative tools
- Target Encoding One Out Row Term
Return a smoothed leave-one-out target-encoding term.
- Missingness Indicator One Cell Token
Recognize a missing-value token under supplied text normalization.