precision_rate
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-06.)
precision_rate is The percentage of retrieved items that are actually among the nearest neighbors..
23 facts·10 predicates·7 sources·3 in dispute
Mostly:rdf:type(7), inverse of(2), description(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (23)
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.
isMeasuredOnIs Measured on(6)
- Annoy 1 18 0
ex:Annoy-1-18-0 - Faiss 1 7 3
ex:Faiss-1-7-3 - Hnswlib 0 9 2
ex:Hnswlib-0-9-2 - Milvus 2 3 0
ex:Milvus-2-3-0 - Qdrant 0 8 1
ex:Qdrant-0-8-1 - Weaviate 1 19 0
ex:Weaviate-1-19-0
hasMemberHas Member(3)
- Performance Metrics
ex:performance-metrics - Performance Metrics Category
ex:performance-metrics-category - Quantitative Factors
ex:quantitative-factors
inputToInput to(2)
- False Positives
ex:false_positives - True Positives
ex:true_positives
calculatesMetricCalculates Metric(1)
- Vector Search Metrics
ex:vector-search-metrics
combinesCombines(1)
- F1 Score
ex:f1-score
containsElementContains Element(1)
- Metrics
ex:metrics
correlatesWithCorrelates With(1)
- Recall Rate
ex:recall-rate
hasMetricHas Metric(1)
- Vector Search Libraries
ex:vector-search-libraries
includesMetricIncludes Metric(1)
- Vector Search Comparison
ex:vector-search-comparison
orderedSuggestionOrdered Suggestion(1)
- Assistant
ex:assistant
storesValueStores Value(1)
- Results
ex:results
suggestedMetricSuggested Metric(1)
- Assistant
ex:assistant
usesMetricUses Metric(1)
- Vector Search Comparison Matrix
ex:vector-search-comparison-matrix
Other facts (17)
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.
17 facts
| Predicate | Value | Ref |
|---|---|---|
| Rdf:type | Performance Metric | [1] |
| Rdf:type | Performance Metric | [2] |
| Rdf:type | Performance Metric | [3] |
| Rdf:type | Quantitative Metric | [4] |
| Rdf:type | Metric | [5] |
| Rdf:type | Metric | [6] |
| Rdf:type | Metric | [7] |
| Inverse of | Recall | [4] |
| Inverse of | Has Precision Rate | [7] |
| Description | The percentage of retrieved items that are actually among the nearest neighbors. | [3] |
| Has Definition | Percentage of retrieved items that are actually among the nearest neighbors | [4] |
| Belongs to List | Quantitative Factors | [4] |
| Relates to | Nearest Neighbors | [4] |
| Formula | true_positives / (true_positives + false_positives) | [6] |
| Component of | F1 Score | [6] |
| Has Unit | ratio | [7] |
| Higher Is Better | true | [7] |
Timeline
Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.
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typebeam/7fe8a152-f4b0-4ead-886d-12532ab7dcc3
ex:PerformanceMetric
—
labelbeam/7fe8a152-f4b0-4ead-886d-12532ab7dcc3
precision_rate
—
typebeam/7962136c-c338-4cc2-87ff-eaf945be2841
ex:PerformanceMetric
—
labelbeam/7962136c-c338-4cc2-87ff-eaf945be2841
precision_rate
—
typebeam/0e56e8f7-6bb5-47d4-bd16-a0b896835d01
ex:PerformanceMetric
—
labelbeam/0e56e8f7-6bb5-47d4-bd16-a0b896835d01
Precision Rate
—
descriptionbeam/0e56e8f7-6bb5-47d4-bd16-a0b896835d01
The percentage of retrieved items that are actually among the nearest neighbors.
—
typebeam/828a477e-11c1-4d56-95a5-65037c8583e2
ex:QuantitativeMetric
—
labelbeam/828a477e-11c1-4d56-95a5-65037c8583e2
Precision Rate
—
hasDefinitionbeam/828a477e-11c1-4d56-95a5-65037c8583e2
Percentage of retrieved items that are actually among the nearest neighbors
—
belongsToListbeam/828a477e-11c1-4d56-95a5-65037c8583e2
ex:quantitative-factors
—
inverseOfbeam/828a477e-11c1-4d56-95a5-65037c8583e2
ex:recall
—
relatesTobeam/828a477e-11c1-4d56-95a5-65037c8583e2
ex:nearest-neighbors
—
typebeam/1ff666a3-024a-43b9-a61b-238256feb9fd
ex:Metric
—
labelbeam/1ff666a3-024a-43b9-a61b-238256feb9fd
Precision Rate
—
typebeam/6dbe8f35-74b9-40c2-9797-0debc6fb19f9
ex:Metric
—
formulabeam/6dbe8f35-74b9-40c2-9797-0debc6fb19f9
true_positives / (true_positives + false_positives)
—
componentOfbeam/6dbe8f35-74b9-40c2-9797-0debc6fb19f9
ex:f1-score
—
typebeam/4839e02a-4d69-40e5-9fd1-d54a40659285
ex:Metric
—
labelbeam/4839e02a-4d69-40e5-9fd1-d54a40659285
precision_rate
—
inverseOfbeam/4839e02a-4d69-40e5-9fd1-d54a40659285
ex:hasPrecisionRate
—
hasUnitbeam/4839e02a-4d69-40e5-9fd1-d54a40659285
ratio
—
higherIsBetterbeam/4839e02a-4d69-40e5-9fd1-d54a40659285
true
References (7)
7 references
ctx:claims/beam/7fe8a152-f4b0-4ead-886d-12532ab7dcc3- full textbeam-chunktext/plain1 KB
doc:beam/7fe8a152-f4b0-4ead-886d-12532ab7dcc3Show excerpt
8. **Ease of Integration**: How easy it is to integrate the database into your existing system. 9. **Community Support**: The level of community support and documentation available. 10. **Cost**: The financial cost associated with using the…
ctx:claims/beam/7962136c-c338-4cc2-87ff-eaf945be2841- full textbeam-chunktext/plain1 KB
doc:beam/7962136c-c338-4cc2-87ff-eaf945be2841Show excerpt
matrix.loc['Annoy 1.18.0', 'memory_usage'] = 600 matrix.loc['Hnswlib 0.9.2', 'memory_usage'] = 580 matrix.loc['Qdrant 0.8.1', 'memory_usage'] = 520 matrix.loc['Weaviate 1.14.0', 'memory_usage'] = 560 matrix.loc['Milvus 2.3.0', 'storage_siz…
ctx:claims/beam/0e56e8f7-6bb5-47d4-bd16-a0b896835d01- full textbeam-chunktext/plain1 KB
doc:beam/0e56e8f7-6bb5-47d4-bd16-a0b896835d01Show excerpt
matrix.loc['Faiss 1.7.3', 'search_time'] = 200 matrix.loc['Annoy 1.18.0', 'search_time'] = 250 matrix.loc['Hnswlib 0.9.2', 'search_time'] = 220 matrix.loc['Qdrant 0.8.1', 'search_time'] = 190 matrix.loc['Weaviate 1.14.0', 'search_time'] = 2…
ctx:claims/beam/828a477e-11c1-4d56-95a5-65037c8583e2- full textbeam-chunktext/plain1 KB
doc:beam/828a477e-11c1-4d56-95a5-65037c8583e2Show excerpt
6. **Precision Rate**: Percentage of retrieved items that are actually among the nearest neighbors. 7. **F1 Score**: Harmonic mean of precision and recall. 8. **Query Latency**: Average time taken to process a query. 9. **Scalability**: How…
ctx:claims/beam/1ff666a3-024a-43b9-a61b-238256feb9fd- full textbeam-chunktext/plain1 KB
doc:beam/1ff666a3-024a-43b9-a61b-238256feb9fdShow excerpt
matrix.loc['Weaviate 1.14.0', 'indexing_time'] = 360 matrix.loc['Milvus 2.3.0', 'memory_usage'] = 500 matrix.loc['Faiss 1.7.3', 'memory_usage'] = 550 matrix.loc['Annoy 1.18.0', 'memory_usage'] = 600 matrix.loc['Hnswlib 0.9.2', 'memory_usag…
ctx:claims/beam/6dbe8f35-74b9-40c2-9797-0debc6fb19f9- full textbeam-chunktext/plain1 KB
doc:beam/6dbe8f35-74b9-40c2-9797-0debc6fb19f9Show excerpt
true_positives = sum([1 for vec in retrieved_neighbors if vec in true_neighbors]) false_positives = len(retrieved_neighbors) - true_positives false_negatives = len(true_neighbors) - true_positives recall_rate = true_positive…
ctx:claims/beam/4839e02a-4d69-40e5-9fd1-d54a40659285
See also
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