ML Model Confidence Scoring System

A ML Model Confidence Scoring System is a scoring system that supports ML model confidence scoring tasks.

• AKA: Model Uncertainty Estimation System, Prediction Confidence System, ML Reliability Scoring System.
• Context:
  • It can typically compute Prediction Confidence Scores using ML uncertainty metrics.
  • It can typically identify Low-Confidence Predictions for ML model review.
  • It can often calibrate Confidence Thresholds through ML validation sets.
  • It can often distinguish Aleatoric Uncertainty from epistemic uncertainty.
  • ...
  • It can range from being a Point-Estimate ML Model Confidence Scoring System to being a Distribution-Based ML Model Confidence Scoring System, depending on its ML confidence representation.
  • It can range from being a Model-Agnostic Confidence Scoring System to being a Model-Specific Confidence Scoring System, depending on its ML model dependency.
  • It can range from being a Binary ML Confidence System to being a Continuous ML Confidence System, depending on its ML confidence granularity.
  • It can range from being a Static ML Confidence Scoring System to being a Adaptive ML Confidence Scoring System, depending on its ML confidence learning.
  • It can range from being a Single-Model Confidence System to being a Ensemble-Based Confidence System, depending on its ML model architecture.
  • ...
  • It can support ML Model Deployment through ML prediction filtering.
  • It can enable Active Learning via ML uncertainty sampling.
  • It can integrate with ML Pipelines for ML confidence monitoring.
  • It can solve ML Model Confidence Scoring Tasks through ML confidence algorithms.
  • ...
• Example(s):
  • Domain-Specific Confidence Systems, such as:
    • Contract Playbook Instruction Confidence Scoring Model for legal rule quality.
    • Medical Diagnosis Confidence System for clinical decision support.
  • Task-Specific Confidence Systems, such as:
    • NER Confidence Scoring System for entity extraction reliability.
    • Classification Confidence System for category prediction certainty.
  • Architecture-Specific Confidence Systems, such as:
    • Neural Network Confidence System using dropout uncertainty.
    • Ensemble Confidence System using prediction variance.
  • ...
• Counter-Example(s):
  • Deterministic Prediction System, which lacks confidence estimation.
  • Binary Classification System, without probability outputs.
  • Rule-Based System, which doesn't quantify uncertainty.
• See: Confidence Scoring Model, Uncertainty Quantification, ML Model Evaluation, Prediction Reliability Metric, Bayesian Neural Network, Calibration Method.

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