🎲  Confidence Level

Confidence Level#

The long-run proportion of intervals expected to contain the true parameter.

Important

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What it is#

A model’s confidence level is the probability it attaches to its prediction — how sure it is that an instance belongs to the predicted class. It is only meaningful if it is calibrated: a model is well-calibrated when predictions made with confidence \(p\) are correct about 100p% of the time (predict 0.9 → right 90% of the time).

How it’s checked#

A reliability diagram bins predictions by confidence level and plots confidence against actual accuracy; perfect calibration lies on the diagonal. The gap is summarized by the Expected Calibration Error (ECE) — the average distance between confidence and accuracy across bins.

Why it matters#

Raw accuracy says nothing about whether the confidence is honest, yet downstream risk-based decisions (which cases to escalate, when to defer) depend on trusting the number. This is the model sense of confidence, distinct from a statistical confidence interval.


Theme: Probability & Statistics Foundations  ·  All terminology



See also

Source article Adapted (context, re-expressed) in our own words from: Confidence Level (insightful-data-lab.com).

Tags: purpose: reference topic: terminology level: beginner