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The Waikato Environment for Knowledge Analysis (WEKA), a machine learning workbench. This version represents the developer version, the "bleeding edge" of development, you could say. New functionality gets added to this version.

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/*
 *   This program is free software: you can redistribute it and/or modify
 *   it under the terms of the GNU General Public License as published by
 *   the Free Software Foundation, either version 3 of the License, or
 *   (at your option) any later version.
 *
 *   This program is distributed in the hope that it will be useful,
 *   but WITHOUT ANY WARRANTY; without even the implied warranty of
 *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *   GNU General Public License for more details.
 *
 *   You should have received a copy of the GNU General Public License
 *   along with this program.  If not, see .
 */

/*
 *    IntervalEstimator.java
 *    Copyright (C) 2005-2012 University of Waikato, Hamilton, New Zealand
 *
 */

package weka.classifiers;

import weka.core.Instance;

/**
 * Interface for numeric prediction schemes that can output prediction
 * intervals.
 *
 * @author Kurt Driessens ([email protected])
 * @version $Revision: 8034 $
 */
public interface IntervalEstimator {

  /**
   * Returns an N * 2 array, where N is the number of prediction
   * intervals. In each row, the first element contains the lower
   * boundary of the corresponding prediction interval and the second
   * element the upper boundary.
   *
   * @param inst the instance to make the prediction for.
   * @param confidenceLevel the percentage of cases that the interval should cover.
   * @return an array of prediction intervals
   * @exception Exception if the intervals can't be computed
   */
  double[][] predictIntervals(Instance inst, double confidenceLevel) throws Exception;
}