Performance Estimation Algorithm

A Performance Estimation Algorithm is an evaluation algorithm that estimates model performance metrics on unseen data.

• AKA: Generalization Performance Estimator, Predictive Performance Algorithm.
• Context:
  • It can (typically) predict Out-of-Sample Performance from available data.
  • It can (typically) quantify Prediction Uncertainty through statistical methods.
  • It can (typically) detect Overfitting through train-test comparisons.
  • It can (typically) provide Confidence Bounds for performance estimates.
  • ...
  • It can (often) trade Computational Cost for estimation accuracy.
  • It can (often) require Independence Assumptions between training and evaluation data.
  • ...
  • It can range from being a Biased Performance Estimation Algorithm to being an Unbiased Performance Estimation Algorithm, depending on its estimation property.
  • It can range from being a Simple Performance Estimation Algorithm to being a Complex Performance Estimation Algorithm, depending on its methodological sophistication.
  • It can range from being a Point Performance Estimation Algorithm to being an Interval Performance Estimation Algorithm, depending on its output type.
  • It can range from being a Single-Metric Performance Estimation Algorithm to being a Multi-Metric Performance Estimation Algorithm, depending on its metric scope.
  • ...
• Example(s):
  • Holdout Performance Estimation Algorithms for single-split evaluation.
  • K-Fold Cross-Validation Algorithms for systematic evaluation.
  • Leave-One-Out Cross-Validation Algorithms for exhaustive evaluation.
  • Bootstrap Performance Estimation Algorithms for confidence intervals.
  • Nested Cross-Validation Algorithms for unbiased estimation.
  • Repeated Cross-Validation Algorithms for variance reduction.
  • ...
• Counter-Example(s):
  • Training Error Algorithms, which evaluate on seen data.
  • Theoretical Bound Algorithms, which derive worst-case guarantees.
  • Simulation-Based Algorithms, which use synthetic data rather than real data.
• See: Model Evaluation Task, Cross-Validation Algorithm, Bootstrap Resampling Algorithm, Statistical Estimation Method, Overfitting Detection Task, Generalization Error, Validation Task.

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