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Class: PerformanceMetrics

General performance metrics

URI: revaise:PerformanceMetrics

```mermaid classDiagram class PerformanceMetrics click PerformanceMetrics href "../PerformanceMetrics/" PerformanceMetrics <|-- AIPerformanceMetrics click AIPerformanceMetrics href "../AIPerformanceMetrics/"

  PerformanceMetrics : accuracy

  PerformanceMetrics : area_under_curve

  PerformanceMetrics : balanced_accuracy

  PerformanceMetrics : diagnostic_odds_ratio

  PerformanceMetrics : f1_score

  PerformanceMetrics : false_discovery_rate

  PerformanceMetrics : false_negative_rate

  PerformanceMetrics : false_omission_rate

  PerformanceMetrics : false_positive_rate

  PerformanceMetrics : matthews_correlation

  PerformanceMetrics : negative_predictive_value

  PerformanceMetrics : precision

  PerformanceMetrics : sensitivity

  PerformanceMetrics : specificity

```

Inheritance

Slots

Name Cardinality and Range Description Inheritance
sensitivity 0..1
Float		 True positive rate (recall) direct
specificity 0..1
Float		 True negative rate direct
precision 0..1
Float		 Positive predictive value direct
negative_predictive_value 0..1
Float		 Negative predictive value direct
false_positive_rate 0..1
Float		 Type I error rate direct
false_negative_rate 0..1
Float		 Type II error rate direct
false_discovery_rate 0..1
Float		 Expected proportion of false discoveries direct
false_omission_rate 0..1
Float		 Proportion of false negatives among negative calls direct
accuracy 0..1
Float		 Overall accuracy direct
balanced_accuracy 0..1
Float		 Average of sensitivity and specificity direct
f1_score 0..1
Float		 Harmonic mean of precision and recall direct
matthews_correlation 0..1
Float		 Matthews correlation coefficient direct
diagnostic_odds_ratio 0..1
Float		 Ratio of odds of positive test in diseased vs non-diseased direct
area_under_curve 0..1
Float		 Area under the ROC curve direct

Identifier and Mapping Information

Schema Source

  • from schema: https://open-and-sustainable.github.io/revaise-model/schema/stages/extraction

Mappings

Mapping Type Mapped Value
self revaise:PerformanceMetrics
native revaise:PerformanceMetrics

LinkML Source

Direct

name: PerformanceMetrics
description: General performance metrics
from_schema: https://open-and-sustainable.github.io/revaise-model/schema/stages/extraction
slots:
- sensitivity
- specificity
- precision
- negative_predictive_value
- false_positive_rate
- false_negative_rate
- false_discovery_rate
- false_omission_rate
- accuracy
- balanced_accuracy
- f1_score
- matthews_correlation
- diagnostic_odds_ratio
- area_under_curve
slot_usage:
  sensitivity:
    name: sensitivity
    description: True positive rate (recall)
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  specificity:
    name: specificity
    description: True negative rate
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  precision:
    name: precision
    description: Positive predictive value
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  negative_predictive_value:
    name: negative_predictive_value
    description: Negative predictive value
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  false_positive_rate:
    name: false_positive_rate
    description: Type I error rate
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  false_negative_rate:
    name: false_negative_rate
    description: Type II error rate
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  false_discovery_rate:
    name: false_discovery_rate
    description: Expected proportion of false discoveries
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  false_omission_rate:
    name: false_omission_rate
    description: Proportion of false negatives among negative calls
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  accuracy:
    name: accuracy
    description: Overall accuracy
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  balanced_accuracy:
    name: balanced_accuracy
    description: Average of sensitivity and specificity
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  f1_score:
    name: f1_score
    description: Harmonic mean of precision and recall
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  matthews_correlation:
    name: matthews_correlation
    description: Matthews correlation coefficient
    range: float
    minimum_value: -1.0
    maximum_value: 1.0
  diagnostic_odds_ratio:
    name: diagnostic_odds_ratio
    description: Ratio of odds of positive test in diseased vs non-diseased
    range: float
    minimum_value: 0.0
  area_under_curve:
    name: area_under_curve
    description: Area under the ROC curve
    range: float
    minimum_value: 0.0
    maximum_value: 1.0

Induced

name: PerformanceMetrics
description: General performance metrics
from_schema: https://open-and-sustainable.github.io/revaise-model/schema/stages/extraction
slot_usage:
  sensitivity:
    name: sensitivity
    description: True positive rate (recall)
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  specificity:
    name: specificity
    description: True negative rate
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  precision:
    name: precision
    description: Positive predictive value
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  negative_predictive_value:
    name: negative_predictive_value
    description: Negative predictive value
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  false_positive_rate:
    name: false_positive_rate
    description: Type I error rate
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  false_negative_rate:
    name: false_negative_rate
    description: Type II error rate
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  false_discovery_rate:
    name: false_discovery_rate
    description: Expected proportion of false discoveries
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  false_omission_rate:
    name: false_omission_rate
    description: Proportion of false negatives among negative calls
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  accuracy:
    name: accuracy
    description: Overall accuracy
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  balanced_accuracy:
    name: balanced_accuracy
    description: Average of sensitivity and specificity
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  f1_score:
    name: f1_score
    description: Harmonic mean of precision and recall
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  matthews_correlation:
    name: matthews_correlation
    description: Matthews correlation coefficient
    range: float
    minimum_value: -1.0
    maximum_value: 1.0
  diagnostic_odds_ratio:
    name: diagnostic_odds_ratio
    description: Ratio of odds of positive test in diseased vs non-diseased
    range: float
    minimum_value: 0.0
  area_under_curve:
    name: area_under_curve
    description: Area under the ROC curve
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
attributes:
  sensitivity:
    name: sensitivity
    description: True positive rate (recall)
    from_schema: https://open-and-sustainable.github.io/revaise-model/schema/stages/extraction
    rank: 1000
    alias: sensitivity
    owner: PerformanceMetrics
    domain_of:
    - PerformanceMetrics
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  specificity:
    name: specificity
    description: True negative rate
    from_schema: https://open-and-sustainable.github.io/revaise-model/schema/stages/extraction
    rank: 1000
    alias: specificity
    owner: PerformanceMetrics
    domain_of:
    - PerformanceMetrics
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  precision:
    name: precision
    description: Positive predictive value
    from_schema: https://open-and-sustainable.github.io/revaise-model/schema/stages/extraction
    rank: 1000
    alias: precision
    owner: PerformanceMetrics
    domain_of:
    - PerformanceMetrics
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  negative_predictive_value:
    name: negative_predictive_value
    description: Negative predictive value
    from_schema: https://open-and-sustainable.github.io/revaise-model/schema/stages/extraction
    rank: 1000
    alias: negative_predictive_value
    owner: PerformanceMetrics
    domain_of:
    - PerformanceMetrics
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  false_positive_rate:
    name: false_positive_rate
    description: Type I error rate
    from_schema: https://open-and-sustainable.github.io/revaise-model/schema/stages/extraction
    rank: 1000
    alias: false_positive_rate
    owner: PerformanceMetrics
    domain_of:
    - PerformanceMetrics
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  false_negative_rate:
    name: false_negative_rate
    description: Type II error rate
    from_schema: https://open-and-sustainable.github.io/revaise-model/schema/stages/extraction
    rank: 1000
    alias: false_negative_rate
    owner: PerformanceMetrics
    domain_of:
    - PerformanceMetrics
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  false_discovery_rate:
    name: false_discovery_rate
    description: Expected proportion of false discoveries
    from_schema: https://open-and-sustainable.github.io/revaise-model/schema/stages/extraction
    rank: 1000
    alias: false_discovery_rate
    owner: PerformanceMetrics
    domain_of:
    - PerformanceMetrics
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  false_omission_rate:
    name: false_omission_rate
    description: Proportion of false negatives among negative calls
    from_schema: https://open-and-sustainable.github.io/revaise-model/schema/stages/extraction
    rank: 1000
    alias: false_omission_rate
    owner: PerformanceMetrics
    domain_of:
    - PerformanceMetrics
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  accuracy:
    name: accuracy
    description: Overall accuracy
    from_schema: https://open-and-sustainable.github.io/revaise-model/schema/stages/extraction
    rank: 1000
    alias: accuracy
    owner: PerformanceMetrics
    domain_of:
    - PerformanceMetrics
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  balanced_accuracy:
    name: balanced_accuracy
    description: Average of sensitivity and specificity
    from_schema: https://open-and-sustainable.github.io/revaise-model/schema/stages/extraction
    rank: 1000
    alias: balanced_accuracy
    owner: PerformanceMetrics
    domain_of:
    - PerformanceMetrics
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  f1_score:
    name: f1_score
    description: Harmonic mean of precision and recall
    from_schema: https://open-and-sustainable.github.io/revaise-model/schema/stages/extraction
    rank: 1000
    alias: f1_score
    owner: PerformanceMetrics
    domain_of:
    - PerformanceMetrics
    range: float
    minimum_value: 0.0
    maximum_value: 1.0
  matthews_correlation:
    name: matthews_correlation
    description: Matthews correlation coefficient
    from_schema: https://open-and-sustainable.github.io/revaise-model/schema/stages/extraction
    rank: 1000
    alias: matthews_correlation
    owner: PerformanceMetrics
    domain_of:
    - PerformanceMetrics
    range: float
    minimum_value: -1.0
    maximum_value: 1.0
  diagnostic_odds_ratio:
    name: diagnostic_odds_ratio
    description: Ratio of odds of positive test in diseased vs non-diseased
    from_schema: https://open-and-sustainable.github.io/revaise-model/schema/stages/extraction
    rank: 1000
    alias: diagnostic_odds_ratio
    owner: PerformanceMetrics
    domain_of:
    - PerformanceMetrics
    range: float
    minimum_value: 0.0
  area_under_curve:
    name: area_under_curve
    description: Area under the ROC curve
    from_schema: https://open-and-sustainable.github.io/revaise-model/schema/stages/extraction
    rank: 1000
    alias: area_under_curve
    owner: PerformanceMetrics
    domain_of:
    - PerformanceMetrics
    range: float
    minimum_value: 0.0
    maximum_value: 1.0