Datasets:
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"field_id": "F046",
"field": "conformal prediction",
"directions": [
{
"direction_id": "G0",
"name": "Coverage-calibrated predictive sets and intervals",
"scope": "Construct and evaluate prediction sets or intervals with coverage guarantees for model predictions, including general-purpose conformal calibration, local calibration for covariate or response heterogeneity, and the use of predictive distributions, representations, classifier information, or region geometry to improve the usefulness of the sets."
},
{
"direction_id": "G1",
"name": "Predictive guarantees for dependent and evolving data",
"scope": "Establish or maintain conformal prediction guarantees under temporal dependence, sequential arrival, or changing observation conditions, including dependence-aware validity, sequential recalibration, and joint prediction regions across a forecasting horizon."
},
{
"direction_id": "G2",
"name": "Conformal loss and decision-risk control",
"scope": "Calibrate predictive outputs, sets, or decisions to guarantee bounds on expected loss, error risk, or decision cost, rather than only guaranteeing that the true outcome falls within a prediction set."
}
]
}
|