ReliabilityModelPlot

class ReliabilityModelPlot[source]

Bases: object

Visualize ReliabilityModel outputs — calibration and the two trust axes.

Turns the tables from ReliabilityModel into a per-sample view — each prediction’s score with its uncertainty interval, colored by trust status (ranking()) — and three batch diagnostics: a calibration curve (reliability_diagram(), from ReliabilityModel.eval()), the out-of-distribution score distribution (ood_hist()), and a score-vs-OOD map colored by the reliable flag (trust_map(); the last three from ReliabilityModel.predict()).

Warning

Experimental. This class is part of the new v1.1.0 prediction layer and is under active development; its API (signatures, defaults, return objects) may change between minor releases without the usual deprecation cycle. Pin a version if you depend on the current behaviour.

Added in version 1.1.0.

See also

Methods

ood_hist(df_rel, *[, figsize, bins, color, ...])

Histogram of the out-of-distribution score, with the in-domain boundary at 1.0.

ranking(df_rel, *[, names, figsize, top_n, ...])

Per-sample view — each prediction's score with its uncertainty, colored by trust status.

reliability_diagram(df_eval, *[, figsize, ...])

Calibration curve — mean predicted score vs.

trust_map(df_rel, *[, figsize, title, ax])

Score vs.