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1   /*
2    * Licensed to the Apache Software Foundation (ASF) under one or more
3    * contributor license agreements.  See the NOTICE file distributed with
4    * this work for additional information regarding copyright ownership.
5    * The ASF licenses this file to You under the Apache License, Version 2.0
6    * (the "License"); you may not use this file except in compliance with
7    * the License.  You may obtain a copy of the License at
8    *
9    *      http://www.apache.org/licenses/LICENSE-2.0
10   *
11   * Unless required by applicable law or agreed to in writing, software
12   * distributed under the License is distributed on an "AS IS" BASIS,
13   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14   * See the License for the specific language governing permissions and
15   * limitations under the License.
16   */
17  
18  package org.apache.commons.math4.legacy.ml.clustering;
19  
20  import java.util.List;
21  
22  /**
23   * Defines a measure of the quality of clusters.
24   */
25  public interface ClusterEvaluator {
26      /**
27       * @param cList List of clusters.
28       * @return the score attributed by the evaluator.
29       */
30      double score(List<? extends Cluster<? extends Clusterable>> cList);
31  
32      /**
33       * Provides a means to interpret the {@link #score(List) score value}.
34       *
35       * @param a Score computed by this evaluator.
36       * @param b Score computed by this evaluator.
37       * @return {@code true} if the evaluator considers that score
38       * {@code a} is better than score {@code b}.
39       */
40      boolean isBetterScore(double a, double b);
41  
42      /**
43       * Converts to a {@link ClusterRanking ranking function}
44       * (as required by clustering implementations).
45       *
46       * @param <T> the type of points that can be clustered
47       * @param eval Evaluator function.
48       * @return a ranking function.
49       */
50      static <T extends Clusterable> ClusterRanking ranking(ClusterEvaluator eval) {
51          return eval.isBetterScore(1, 2) ?
52              clusters -> 1 / eval.score(clusters) :
53              clusters -> eval.score(clusters);
54      }
55  }