Class: PredictionSummaryStatistics

A class for collecting totals of various outcomes.

URI: linkml_common:PredictionSummaryStatistics

classDiagram class PredictionSummaryStatistics click PredictionSummaryStatistics href "../PredictionSummaryStatistics" OutcomeStatistics <|-- PredictionSummaryStatistics click OutcomeStatistics href "../OutcomeStatistics" Intangible <|-- PredictionSummaryStatistics click Intangible href "../Intangible" PredictionSummaryStatistics : accuracy PredictionSummaryStatistics : f1_score PredictionSummaryStatistics : false_negative_count PredictionSummaryStatistics : false_positive_count PredictionSummaryStatistics : precision PredictionSummaryStatistics : predictions PredictionSummaryStatistics --> "*" Prediction : predictions click Prediction href "../Prediction" PredictionSummaryStatistics : recall PredictionSummaryStatistics : true_negative_count PredictionSummaryStatistics : true_positive_count PredictionSummaryStatistics : type PredictionSummaryStatistics : uses_dataset PredictionSummaryStatistics --> "0..1" Dataset : uses_dataset click Dataset href "../Dataset"

Inheritance

Entity [ Typed]
- Intangible
  - PredictionSummaryStatistics [ OutcomeStatistics]

Slots

Name	Cardinality and Range	Description	Inheritance
predictions	* Prediction		direct
uses_dataset	0..1 Dataset		direct
true_positive_count	0..1 CountScalar	Total number of true positives (TP)	OutcomeStatistics
false_positive_count	0..1 CountScalar	Total number of false positives (FP)	OutcomeStatistics
true_negative_count	0..1 CountScalar	Total number of true negatives (TN)	OutcomeStatistics
false_negative_count	0..1 CountScalar	Total number of false negatives (FN)	OutcomeStatistics
recall	0..1 Float	Recall is calculated as TP / (TP + FN)	OutcomeStatistics
precision	0..1 Float	Precision is calculated as TP / (TP + FP)	OutcomeStatistics
f1_score	0..1 Float	F1 Score is the harmonic mean of precision and recall	OutcomeStatistics
accuracy	0..1 Float	Accuracy is calculated as (TP + TN) / (TP + FP + TN + FN)	OutcomeStatistics
type	0..1 String	A type for a thing	Typed

Identifier and Mapping Information

Schema Source

from schema: https://w3id.org/linkml/linkml-common

Mappings

Mapping Type	Mapped Value
self	linkml_common:PredictionSummaryStatistics
native	linkml_common:PredictionSummaryStatistics

LinkML Source

Direct

name: PredictionSummaryStatistics
description: A class for collecting totals of various outcomes.
from_schema: https://w3id.org/linkml/linkml-common
is_a: Intangible
mixins:
- OutcomeStatistics
attributes:
  predictions:
    name: predictions
    from_schema: https://w3id.org/linkml-common/statistics
    rank: 1000
    domain_of:
    - PredictionSummaryStatistics
    range: Prediction
    multivalued: true
    inlined: true
    inlined_as_list: true
  uses_dataset:
    name: uses_dataset
    from_schema: https://w3id.org/linkml-common/statistics
    rank: 1000
    domain_of:
    - PredictionSummaryStatistics
    range: Dataset

Induced

name: PredictionSummaryStatistics
description: A class for collecting totals of various outcomes.
from_schema: https://w3id.org/linkml/linkml-common
is_a: Intangible
mixins:
- OutcomeStatistics
attributes:
  predictions:
    name: predictions
    from_schema: https://w3id.org/linkml-common/statistics
    rank: 1000
    alias: predictions
    owner: PredictionSummaryStatistics
    domain_of:
    - PredictionSummaryStatistics
    range: Prediction
    multivalued: true
    inlined: true
    inlined_as_list: true
  uses_dataset:
    name: uses_dataset
    from_schema: https://w3id.org/linkml-common/statistics
    rank: 1000
    alias: uses_dataset
    owner: PredictionSummaryStatistics
    domain_of:
    - PredictionSummaryStatistics
    range: Dataset
  true_positive_count:
    name: true_positive_count
    description: Total number of true positives (TP)
    from_schema: https://w3id.org/linkml-common/statistics
    rank: 1000
    alias: true_positive_count
    owner: PredictionSummaryStatistics
    domain_of:
    - OutcomeStatistics
    range: CountScalar
  false_positive_count:
    name: false_positive_count
    description: Total number of false positives (FP)
    from_schema: https://w3id.org/linkml-common/statistics
    rank: 1000
    alias: false_positive_count
    owner: PredictionSummaryStatistics
    domain_of:
    - OutcomeStatistics
    range: CountScalar
  true_negative_count:
    name: true_negative_count
    description: Total number of true negatives (TN)
    from_schema: https://w3id.org/linkml-common/statistics
    rank: 1000
    alias: true_negative_count
    owner: PredictionSummaryStatistics
    domain_of:
    - OutcomeStatistics
    range: CountScalar
  false_negative_count:
    name: false_negative_count
    description: Total number of false negatives (FN)
    from_schema: https://w3id.org/linkml-common/statistics
    rank: 1000
    alias: false_negative_count
    owner: PredictionSummaryStatistics
    domain_of:
    - OutcomeStatistics
    range: CountScalar
  recall:
    name: recall
    description: Recall is calculated as TP / (TP + FN)
    from_schema: https://w3id.org/linkml-common/statistics
    rank: 1000
    alias: recall
    owner: PredictionSummaryStatistics
    domain_of:
    - OutcomeStatistics
    range: float
    equals_expression: (true_positives) / (true_positives + false_negatives)
  precision:
    name: precision
    description: Precision is calculated as TP / (TP + FP)
    from_schema: https://w3id.org/linkml-common/statistics
    rank: 1000
    alias: precision
    owner: PredictionSummaryStatistics
    domain_of:
    - OutcomeStatistics
    range: float
    equals_expression: (true_positives) / (true_positives + false_positives)
  f1_score:
    name: f1_score
    description: F1 Score is the harmonic mean of precision and recall
    from_schema: https://w3id.org/linkml-common/statistics
    rank: 1000
    alias: f1_score
    owner: PredictionSummaryStatistics
    domain_of:
    - OutcomeStatistics
    range: float
    equals_expression: 2 * (precision * recall) / (precision + recall)
  accuracy:
    name: accuracy
    description: Accuracy is calculated as (TP + TN) / (TP + FP + TN + FN)
    from_schema: https://w3id.org/linkml-common/statistics
    rank: 1000
    alias: accuracy
    owner: PredictionSummaryStatistics
    domain_of:
    - OutcomeStatistics
    range: float
    equals_expression: (true_positives + true_negatives) / (true_positives + false_positives
      + true_negatives + false_negatives)
  type:
    name: type
    description: A type for a thing. The range of this should be a class within the
      schema. It is intended for schema-based classification. Anything beneath the
      shoreline of the schema should use `classification`.
    from_schema: https://w3id.org/linkml/linkml-common
    rank: 1000
    designates_type: true
    alias: type
    owner: PredictionSummaryStatistics
    domain_of:
    - Typed
    range: string