<NME> GreedyInitializerTest.java
<BEF> ADDFILE
<MSG> GreedyInitializerTest

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+package edu.neu.ccs.pyramid.multilabel_classification.bmm_variant;
+
+import edu.neu.ccs.pyramid.configuration.Config;
+import edu.neu.ccs.pyramid.dataset.DataSetType;
+import edu.neu.ccs.pyramid.dataset.MultiLabelClfDataSet;
+import edu.neu.ccs.pyramid.dataset.TRECFormat;
+import edu.neu.ccs.pyramid.eval.Accuracy;
+import edu.neu.ccs.pyramid.eval.Overlap;
+
+import java.io.File;
+
+import static org.junit.Assert.*;
+
+public class GreedyInitializerTest {
+    private static final Config config = new Config("config/local.config");
+    private static final String DATASETS = config.getString("input.datasets");
+    private static final String TMP = config.getString("output.tmp");
+    public static void main(String[] args) throws Exception{
+        test1();
+    }
+
+    private static void test1() throws Exception{
+        MultiLabelClfDataSet dataSet = TRECFormat.loadMultiLabelClfDataSet(new File(DATASETS, "/spam/trec_data/train.trec"),
+                DataSetType.ML_CLF_SPARSE, true);
+        MultiLabelClfDataSet testSet = TRECFormat.loadMultiLabelClfDataSet(new File(DATASETS, "/spam/trec_data/test.trec"),
+                DataSetType.ML_CLF_SPARSE, true);
+        int numClusters = 10;
+        double variance = 1000;
+        GreedyInitializer greedyInitializer = new GreedyInitializer(dataSet,numClusters,variance);
+        greedyInitializer.train();
+        System.out.println(greedyInitializer);
+    }
+}
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GreedyInitializerTest