normalize_scores
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-08.)
normalize_scores is Normalize scores to the range [0, 1].
Mostly:uses variable(4), calls(3), rdf:type(2)
Maturity scale
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Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.
callsFunctionCalls Function(2)
- Hybrid Ranking
ex:hybrid-ranking - Hybrid Ranking
ex:hybrid-ranking
containsFunctionContains Function(2)
- Code Block
ex:code-block - Python Logging Example
ex:python-logging-example
callsCalls(1)
- Hybrid Ranking
ex:hybrid-ranking
recommendsActionRecommends Action(1)
- Normalization Suggestion
ex:normalization-suggestion
Other facts (36)
The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.
| Predicate | Value | Ref |
|---|---|---|
| Uses Variable | Min Score Variable | [1] |
| Uses Variable | Max Score Variable | [1] |
| Uses Variable | min_score | [2] |
| Uses Variable | max_score | [2] |
| Calls | Np Min | [2] |
| Calls | Np Max | [2] |
| Calls | Np Zeros Like | [2] |
| Rdf:type | Function | [1] |
| Rdf:type | Function | [2] |
| Returns | Normalized Scores | [1] |
| Returns | Normalized Scores Array | [2] |
| Purpose | Score Normalization | [1] |
| Parameter | Scores | [1] |
| Docstring | Normalize scores to the range [0, 1]. | [1] |
| Handles Edge Case | Identical Scores | [1] |
| Returns Type | Normalized Scores | [1] |
| Contains Conditional | Edge Case Check | [1] |
| Function Definition | Python Def | [1] |
| Handles | Constant Array | [1] |
| Has Parameter | Scores Parameter | [2] |
| Return Type | Numpy Array | [2] |
| Performs Operation | Score Normalization | [2] |
| Description | Normalize scores to the range [0, 1] | [2] |
| Has Condition | Max Equals Min Condition | [2] |
| Returns on Condition | Zeros Array | [2] |
| Called by | Hybrid Ranking | [2] |
| Has Docstring | Normalize scores to the range [0, 1]. | [2] |
| Performs Subtraction | Scores Minus Min | [2] |
| Performs Division | Result Divided by Range | [2] |
| Parameter Count | 1 | [2] |
| First Operation | Calculate Min | [2] |
| Second Operation | Calculate Max | [2] |
| Third Operation | Check Equality | [2] |
| Fourth Operation | Return Zeros or Normalized | [2] |
| Input Type | Score Array | [2] |
| Prevents Division by Zero | true | [2] |
Timeline
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References (2)
ctx:claims/beam/f7999e0a-925c-4a2e-afc4-b5e2483ddb0a- full textbeam-chunktext/plain1 KB
doc:beam/f7999e0a-925c-4a2e-afc4-b5e2483ddb0aShow excerpt
3. **Evaluation Metrics**: Use appropriate evaluation metrics to measure the relevance lift. Common metrics include Precision@k, Recall, and Mean Average Precision (MAP). 4. **Post-processing**: Consider post-processing steps such as re-ra…
ctx:claims/beam/ea094bd1-364b-4b3a-8196-25cc9a2aa87c
See also
- Function
- Score Normalization
- Scores
- Identical Scores
- Normalized Scores
- Edge Case Check
- Min Score Variable
- Max Score Variable
- Python Def
- Constant Array
- Function
- Scores Parameter
- Normalized Scores Array
- Numpy Array
- Max Equals Min Condition
- Zeros Array
- Hybrid Ranking
- Np Min
- Np Max
- Np Zeros Like
- Scores Minus Min
- Result Divided by Range
- Calculate Min
- Calculate Max
- Check Equality
- Return Zeros or Normalized
- Score Array
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