Error Weighting Metric
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An Error Weighting Metric is an error metric that assigns differential importance to errors based on severity, impact, or business risk.
- AKA: Weighted Error Measure, Severity-Based Error Metric, Risk-Adjusted Error Metric.
- Context:
- It can typically prioritize High-Impact Errors with severity weights and risk factors.
- It can typically distinguish Critical Errors from minor discrepancies through impact scoring.
- It can typically support Risk-Based Evaluation via business impact assessment and compliance weighting.
- It can often integrate into Risk-Weighted Scorecards with model error severity and quality metrics.
- It can often enable Cost-Sensitive Learning through misclassification costs and error penaltys.
- It can often inform Model Optimization by focusing improvement on high-weight errors.
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- It can range from being a Low-Severity Error Weighting Metric to being a High-Severity Error Weighting Metric, depending on its error weighting impact threshold.
- It can range from being a Binary Error Weighting Metric to being a Continuous Error Weighting Metric, depending on its error weighting granularity.
- It can range from being a Static Error Weighting Metric to being a Dynamic Error Weighting Metric, depending on its error weighting adaptability.
- It can range from being a Domain-Agnostic Error Weighting Metric to being a Domain-Specific Error Weighting Metric, depending on its error weighting application context.
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- It can complement Mean Squared Error (MSE) Measure with weighted penaltys.
- It can enhance Standard Error Measure through importance factors.
- It can improve Root Mean Squared Error (RMSE) Metric via severity adjustment.
- It can refine Word Error Rate (WER) Measure with linguistic importance.
- It can augment Symmetric Mean Absolute Percentage Error through business criticality.
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- Example(s):
- Severity-Weighted Error Metrics, such as:
- Severity-Weighted Error, which applies severity coefficients to prediction errors.
- Model Error Severity, which categorizes error impact levels.
- Critical Error Penalty, which heavily penalizes safety-critical errors.
- Cost-Based Error Metrics, such as:
- Misclassification Cost Matrix, which assigns monetary costs to error types.
- Business Impact Error Score, which weights by revenue impact.
- Operational Risk Error Metric, which considers operational consequences.
- Domain-Specific Weighted Errors, such as:
- Medical Diagnosis Error Weight, which prioritizes false negatives in critical conditions.
- Financial Risk Error Metric, which emphasizes regulatory violations.
- Legal Document Error Weight, which focuses on liability-creating errors.
- Adaptive Error Weights, such as:
- Time-Sensitive Error Weight, which increases weight over time.
- Context-Aware Error Weight, which adjusts based on application context.
- User-Specific Error Weight, which personalizes error importance.
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- Severity-Weighted Error Metrics, such as:
- Counter-Example(s):
- Unweighted Error Metric, which treats all errors equally regardless of impact.
- Binary Error Count, which only counts presence/absence without weighting.
- Simple Accuracy Metric, which doesn't differentiate error types or severity.
- See: Error Metric, Loss Function, Evaluation Metric, Performance Metric, Mean Squared Error (MSE) Measure, Standard Error (SE) Measure, Root Mean Squared Error (RMSE) Metric, Model Quality Gap, Risk-Weighted Scorecard, Word Error Rate (WER) Measure.