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Jev glossary

Evaluation & TrainingSigmoid calibration

Platt scaling

A two-parameter sigmoid fit on labeled data that maps a model's raw probability onto a better-calibrated one.
Category
Evaluation & Training
Also known as
Sigmoid calibration
Reading time
1 min
Related terms
4
Directory entries
2
Docs
Not listed
Added
2026-09-28

Definition

On 8,801 sentiment examples, Jev's raw expected calibration error for P(positive) was 0.117. A Platt curve fit on a calibration split cut that to 0.052 on held-out data. Isotonic regression on the same split reached 0.008, because the error was not sigmoid-shaped.

The AITA study used a related idea: a logistic regression learned from Jev's answers on 300 older posts, then adjusted probabilities on the 770 test posts. That chart is not a like-for-like win unless every model is adjusted the same way.

Tagscalibrationevaluation

From the Jev directory

Directory entries that go deeper on this term.

A sentiment study of whether Jev's stated confidence matches accuracy, comparing raw scores with Platt scaling and isotonic regression.
Jev Benchmarks & Evaluations#community#python#evaluation
A 770-post benchmark that scores Jev, Sonnet 5, GPT-5 nano, and two local models on Reddit verdicts with weighted Brier scores.
Jev Benchmarks & Evaluations#community#python#evaluation

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