source: branches/MetisMQI/src/main/java/weka/classifiers/evaluation/Prediction.java @ 32

Last change on this file since 32 was 29, checked in by gnappo, 14 years ago

Taggata versione per la demo e aggiunto branch.

File size: 1.8 KB
Line 
1/*
2 *    This program is free software; you can redistribute it and/or modify
3 *    it under the terms of the GNU General Public License as published by
4 *    the Free Software Foundation; either version 2 of the License, or
5 *    (at your option) any later version.
6 *
7 *    This program is distributed in the hope that it will be useful,
8 *    but WITHOUT ANY WARRANTY; without even the implied warranty of
9 *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
10 *    GNU General Public License for more details.
11 *
12 *    You should have received a copy of the GNU General Public License
13 *    along with this program; if not, write to the Free Software
14 *    Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
15 */
16
17/*
18 *    Prediction.java
19 *    Copyright (C) 2002 University of Waikato, Hamilton, New Zealand
20 *
21 */
22
23package weka.classifiers.evaluation;
24
25/**
26 * Encapsulates a single evaluatable prediction: the predicted value plus the
27 * actual class value.
28 *
29 * @author Len Trigg (len@reeltwo.com)
30 * @version $Revision: 5987 $
31 */
32public interface Prediction {
33
34  /**
35   * Constant representing a missing value. This should have the same value
36   * as weka.core.Instance.MISSING_VALUE
37   */
38  double MISSING_VALUE
39    = weka.core.Utils.missingValue();
40
41  /**
42   * Gets the weight assigned to this prediction. This is typically the weight
43   * of the test instance the prediction was made for.
44   *
45   * @return the weight assigned to this prediction.
46   */
47  double weight();
48
49  /**
50   * Gets the actual class value.
51   *
52   * @return the actual class value, or MISSING_VALUE if no
53   * prediction was made. 
54   */
55  double actual();
56
57  /**
58   * Gets the predicted class value.
59   *
60   * @return the predicted class value, or MISSING_VALUE if no
61   * prediction was made. 
62   */
63  double predicted();
64
65}
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