/**
 * Confidence Calibration for Drift Detection
 *
 * Calibrates raw confidence scores to match actual accuracy.
 * A calibrated confidence of 80% means the algorithm is correct ~80% of the time
 * when it reports that confidence level.
 *
 * Calibration is based on evaluation against the golden dataset.
 */
/**
 * Calibration bucket defining expected accuracy for a confidence range.
 */
export interface CalibrationBucket {
    /** Minimum confidence in this bucket (inclusive) */
    min: number;
    /** Maximum confidence in this bucket (exclusive) */
    max: number;
    /** Calibrated accuracy for this bucket */
    calibratedAccuracy: number;
    /** Number of samples used to calculate this bucket */
    sampleCount: number;
}
/**
 * Default calibration model based on golden dataset evaluation.
 *
 * These values should be updated as the algorithm improves.
 * Current baseline: v1.0.1 (50 test cases)
 */
export declare const DEFAULT_CALIBRATION_MODEL: CalibrationBucket[];
/**
 * Calibrate a raw confidence score to reflect actual accuracy.
 *
 * @param rawScore - Raw confidence score (0-100)
 * @param model - Calibration model to use (defaults to DEFAULT_CALIBRATION_MODEL)
 * @returns Calibrated confidence score
 */
export declare function calibrateConfidence(rawScore: number, model?: CalibrationBucket[]): number;
/**
 * Format confidence score with calibration information.
 *
 * @param rawScore - Raw confidence score
 * @param showRaw - Whether to show raw score alongside calibrated
 * @returns Formatted string
 */
export declare function formatCalibratedConfidence(rawScore: number, showRaw?: boolean): string;
/**
 * Get confidence label based on calibrated score.
 */
export declare function getCalibratedConfidenceLabel(rawScore: number): 'high' | 'medium' | 'low' | 'very-low';
/**
 * Check if a calibrated confidence meets a threshold.
 *
 * @param rawScore - Raw confidence score
 * @param threshold - Minimum required calibrated confidence
 * @returns True if calibrated confidence meets threshold
 */
export declare function meetsCalibratedThreshold(rawScore: number, threshold: number): boolean;
/**
 * Update calibration model based on evaluation results.
 * This recalculates accuracy for each bucket from test results.
 *
 * @param results - Array of {predictedConfidence, wasCorrect} pairs
 * @returns Updated calibration model
 */
export declare function updateCalibrationModel(results: Array<{
    predictedConfidence: number;
    wasCorrect: boolean;
}>): CalibrationBucket[];
/**
 * Calculate calibration error (ECE - Expected Calibration Error).
 * Lower is better. 0 = perfectly calibrated.
 *
 * @param model - Calibration model
 * @returns ECE as a percentage (0-100)
 */
export declare function calculateCalibrationError(model: CalibrationBucket[]): number;
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