Datumbox Stepwise Issue

import com.datumbox.common.dataobjects.AssociativeArray;
import com.datumbox.common.dataobjects.Dataset;
import com.datumbox.common.dataobjects.Record;
import com.datumbox.common.persistentstorage.ConfigurationFactory;
import com.datumbox.common.persistentstorage.interfaces.DatabaseConfiguration;
import com.datumbox.framework.machinelearning.regression.MatrixLinearRegression;
import com.datumbox.framework.machinelearning.regression.StepwiseRegression;
import com.SV.aggregate.DailyAggregate;
import org.joda.time.DateTime;

import java.util.ArrayList;
import java.util.Map;

public class Stepwise implements Regression {
    private StepwiseRegression sw = null;
    private Dataset trainingData = null;
    private StepwiseRegression.TrainingParameters trainingParameters = null;
    private DateTime simulatedTime = null;
    private final DatabaseConfiguration dbConf = ConfigurationFactory.INMEMORY.getConfiguration();


    public Stepwise (ArrayList<DailyAggregate> aggregates, ArrayList<String> allowedKeys, DateTime time) {
        this.sw = new StepwiseRegression("DW", dbConf);
        this.simulatedTime = time;

        this.trainingData = new Dataset(dbConf);
        for (DailyAggregate a : aggregates) {
            Map<Object, Object> map = a.toMapWithAllowedKeys(allowedKeys);
            AssociativeArray arr = new AssociativeArray(map);
            Record r = new Record(arr, a.getValue());
            this.trainingData.add(r);
        }

        trainingParameters = new StepwiseRegression.TrainingParameters();
        trainingParameters.setRegressionClass(MatrixLinearRegression.class);
    }
    public RegressionModel generateModel() {
        sw.fit(trainingData, trainingParameters);
        return null;
    }

    public double predict(DailyAggregate aggregate, ArrayList<String> allowedKeys) {
        Map<Object, Object> map = aggregate.toMapWithAllowedKeys(allowedKeys);
        AssociativeArray arr = new AssociativeArray(map);
        // If we're looking to predict Y here, what do we set the value to?
        Record r = new Record(arr, 0d);
        Dataset d = new Dataset(dbConf);
        d.add(r);

        sw.predict(d);
        sw.getValidationMetrics();
        double predicted = Double.parseDouble((String)r.getYPredicted());
        return predicted;
    }
}