WEKA Forecasting Plugin

Question

My question is related to Weka Forecasting Plugin. I'm trying to predict the value of sin(x) in a prediction horizon of 6 using Weka Forecaster, the algorithm is SMOReg, and I'm trying to use different lags ( 1 - 24 ). I'm using a loop for that. The program I wrote is working perfectly but the problem is the results I obtain from my program are different than using Weka GUI directly and I don't know why? Any ideas?

I made sure to use the same "options" of the algorithm but still results are different.

Here's the code:

import java.io.*;
import java.util.*;
import java.util.List;
import weka.core.Instances;
import weka.classifiers.Evaluation;
import weka.classifiers.functions.*;
import weka.classifiers.rules.*;
import weka.classifiers.meta.*;
import weka.classifiers.trees.*;
import weka.classifiers.evaluation.NumericPrediction;
import weka.classifiers.timeseries.WekaForecaster;
import weka.classifiers.timeseries.core.TSLagMaker;
import weka.classifiers.timeseries.core.TSLagMaker.Periodicity;
import weka.classifiers.timeseries.eval.TSEvaluation;
import weka.classifiers.timeseries.eval.ErrorModule;
import weka.core.converters.ConverterUtils.DataSource;

public class TimeSeriesSin {
    static Scanner console = new Scanner(System.in);
    public static void main(String[] args) throws FileNotFoundException{
        try {
            String pathToSinData = "C:/Users/khouloud/Desktop/AUSmaster/thesis/summer/chapter1/sin_10.arff";

            PrintWriter out = new PrintWriter("C:/Users/khouloud/Desktop/AUSmaster/thesis/summer/chapter1/try_sin_10.txt");

            DataSource source = new DataSource(pathToSinData);
            Instances diab = source.getDataSet();

            for(int i = 1; i <= 24; i++) {
                WekaForecaster forecaster = new WekaForecaster();
                forecaster.setFieldsToForecast("sin");
                SMOreg tr = new SMOreg();

                String options = "weka.classifiers.functions.SMOreg -C 1.0 -N 0 -I \"weka.classifiers.functions.supportVector.RegSMOImproved -L 0.001 -W 1 -P 1.0E-12 -T 0.001 -V\" -K \"weka.classifiers.functions.supportVector.PolyKernel -C 250007 -E 1.0\"";
                tr.setOptions(weka.core.Utils.splitOptions(options));

                forecaster.setBaseForecaster(tr);
                forecaster.getTSLagMaker().setMinLag(1);

                forecaster.getTSLagMaker().setMaxLag(i);
                forecaster.buildForecaster(diab, System.out);
                forecaster.primeForecaster(diab);
                List<List<NumericPrediction>> forecast = forecaster.forecast(6, System.out);

                TSEvaluation eval = new TSEvaluation(diab, 0.3);
                eval.setHorizon(6);
                eval.setEvaluateOnTestData(true);
                eval.setEvaluateOnTrainingData(false);
                eval.evaluateForecaster(forecaster, System.out);
                out.println("lag= " + i);
                out.println(eval.toSummaryString()); 
            }

            out.close();
        } catch (Exception ex) {
            ex.printStackTrace();
        }
    }
}

Answer 1

I got the same problem for forecasting three different variables. I used MLPRegressor and SMOreg.

I checked the package version of the pdm-timseriesforecasting package from WEKA-GUI in the Package Manager and put the same package versions in my WEKA-code (I was using a maven repository for my code implementation) and the problem was solved.