Precision P-Value Calculation Method
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A Precision P-Value Calculation Method is a statistical hypothesis testing method that computes p-values for precision scores using standard error estimates from true positives and false positives.
- AKA: Precision Significance Test Method, Positive Predictive Value P-Value Method, Precision Hypothesis Test, Precision Statistical Test Method.
- Context:
- It can typically compute precision = TP/(TP+FP) and derive standard error.
- It can typically test against baseline precision or random classifier precision.
- It can typically use binomial proportion theory for variance estimation.
- It can often apply continuity corrections for small sample sizes.
- It can often support one-sided tests for minimum precision requirements.
- It can often complement F1 P-Value Calculation Methods in comprehensive evaluation.
- It can range from being an Exact Precision P-Value Calculation Method to being an Approximate Precision P-Value Calculation Method, depending on its distributional assumption.
- It can range from being a Single-Class Precision P-Value Calculation Method to being a Multi-Class Precision P-Value Calculation Method, depending on its classification scope.
- It can range from being a Conservative Precision P-Value Calculation Method to being a Liberal Precision P-Value Calculation Method, depending on its variance estimate.
- It can range from being a Independent Precision P-Value Calculation Method to being a Paired Precision P-Value Calculation Method, depending on its sample relationship.
- ...
- Example(s):
- Binary Classifier Precision Tests, such as:
- TP=90, FP=10 → Precision=0.9, SE≈0.03, testing against null=0.5.
- Medical test precision: must significantly exceed 0.95 threshold.
- Multi-Class Macro Precision Tests, such as:
- Average precision across 10 classes tested for significance.
- Per-class precision tests with multiple testing correction.
- Model Comparison Precision Tests, such as:
- Comparing two models' precision on same test set.
- Paired difference test for precision improvement.
- ...
- Binary Classifier Precision Tests, such as:
- Counter-Example(s):
- Recall P-Value Calculation Method, which tests sensitivity.
- F1 P-Value Calculation Method, which tests harmonic mean.
- Accuracy P-Value Method, which tests overall correctness.
- See: Statistical Hypothesis Testing Method, Precision Measure, P-Value Calculation Method, Binomial Proportion Test, True Positive, False Positive, F1 P-Value Calculation Method, Recall P-Value Calculation Method, Performance Measure Computation Method, Continuity Correction in Performance Measure Method, Classification Performance Evaluation.