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Slot: Cross-Validated R² (cv_r2)

Cross-validated R² for the model as a whole.

Why this slot matters

The single most comparable headline number for model skill. Without it a consumer cannot weigh this product against an alternative, or decide whether the model is good enough for the health analysis at hand.

In plain terms

A 0-to-1 score of how well the model's predictions matched reality on data it was not trained on — 1 is perfect, 0 is no better than always guessing the average. "Cross-validated" means the test used held-out data, so the score is honest.

URI: envar:slot/cv_r2

Applicable Classes

Name Description Modifies Slot
ModelAggregateUncertainty Whole-model uncertainty summary — cross-validation metrics and the reference ... no

Properties

Type and Range

Property Value
Range Float
Domain Of ModelAggregateUncertainty

Cardinality and Requirements

Property Value
### Slot Characteristics
Property Value
Owner ModelAggregateUncertainty

Examples

Value
0.86

Identifier and Mapping Information

Annotations

property value
justification The single most comparable headline number for model skill. Without it a consumer cannot weigh this product against an alternative, or decide whether the model is good enough for the health analysis at hand.
explanation A 0-to-1 score of how well the model's predictions matched reality on data it was not trained on — 1 is perfect, 0 is no better than always guessing the average. "Cross-validated" means the test used held-out data, so the score is honest.

Schema Source

Mappings

Mapping Type Mapped Value
self envar:cv_r2
native envar:cv_r2

LinkML Source

name: cv_r2
annotations:
  justification:
    tag: justification
    value: The single most comparable headline number for model skill. Without it
      a consumer cannot weigh this product against an alternative, or decide whether
      the model is good enough for the health analysis at hand.
  explanation:
    tag: explanation
    value: A 0-to-1 score of how well the model's predictions matched reality on data
      it was not trained on — 1 is perfect, 0 is no better than always guessing the
      average. "Cross-validated" means the test used held-out data, so the score is
      honest.
description: Cross-validated R² for the model as a whole.
title: Cross-Validated R²
examples:
- value: '0.86'
  description: Di et al. ensemble PM2.5
from_schema: https://w3id.org/linkml/microschemas/envar
rank: 1000
owner: ModelAggregateUncertainty
domain_of:
- ModelAggregateUncertainty
range: float