<NME> RidgeLRTrainerTest.java
<BEF> ADDFILE
<MSG> add class RidgeLRTrainer

<DFF> @@ -0,0 +1,49 @@
+package edu.neu.ccs.pyramid.classification.logistic_regression;
+
+import edu.neu.ccs.pyramid.classification.boosting.lktb.LKTBConfig;
+import edu.neu.ccs.pyramid.classification.boosting.lktb.LKTreeBoost;
+import edu.neu.ccs.pyramid.configuration.Config;
+import edu.neu.ccs.pyramid.dataset.ClfDataSet;
+import edu.neu.ccs.pyramid.dataset.DataSetType;
+import edu.neu.ccs.pyramid.dataset.TRECFormat;
+import edu.neu.ccs.pyramid.eval.Accuracy;
+import org.apache.commons.lang3.time.StopWatch;
+
+import java.io.File;
+import java.util.List;
+
+import static org.junit.Assert.*;
+
+public class RidgeLRTrainerTest {
+    private static final Config config = new Config("configs/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{
+        spam_build();
+    }
+
+    static void spam_build() throws Exception{
+
+
+        ClfDataSet dataSet = TRECFormat.loadClfDataSet(new File(DATASETS, "/spam/trec_data/train.trec"),
+                DataSetType.CLF_DENSE, true);
+        System.out.println(dataSet.getMetaInfo());
+
+        StopWatch stopWatch = new StopWatch();
+        stopWatch.start();
+        LogisticRegression logisticRegression = RidgeLRTrainer.train(dataSet,10);
+        System.out.println(logisticRegression.weights);
+        stopWatch.stop();
+        System.out.println(stopWatch);
+
+//        for (int i=0;i<dataSet.getNumDataPoints();i++){
+//            System.out.println(logisticRegression.predict(dataSet.getRow(i)));
+//        }
+
+        System.out.println("accuracy="+Accuracy.accuracy(logisticRegression,dataSet));
+
+
+    }
+
+}
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add class RidgeLRTrainer