Java tutorial
/******************************************************************************* * Copyright 2016 * Ubiquitous Knowledge Processing (UKP) Lab * Technische Universitt Darmstadt * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. ******************************************************************************/ package org.dkpro.tc.evaluation.measures.regression; import java.util.Arrays; import java.util.HashMap; import java.util.Map; import org.apache.commons.lang.ArrayUtils; import org.dkpro.tc.evaluation.Id2Outcome; import de.tudarmstadt.ukp.dkpro.statistics.correlation.SpearmansRankCorrelation; public class SpearmanCorrelation { public static Map<String, Double> calculate(Id2Outcome id2Outcome) { Map<String, Double> results = new HashMap<String, Double>(); Double[] goldstandard = ArrayUtils.toObject(id2Outcome.getGoldValues()); Double[] prediction = ArrayUtils.toObject(id2Outcome.getPredictions()); results.put(SpearmanCorrelation.class.getSimpleName(), SpearmansRankCorrelation .computeCorrelation(Arrays.asList(goldstandard), Arrays.asList(prediction))); return results; } }