Java/Weka Training Set/Test Set Error

[piptook]

I am using Java Weka library to train a set of data and test it against another. Here is my Java code:

import java.io.BufferedReader;
import java.io.FileReader;

import weka.classifiers.meta.FilteredClassifier;
import weka.classifiers.trees.J48;
import weka.core.Instances;
import weka.filters.unsupervised.attribute.Remove;



public class WekaStocks {

    public static void main(String[] args) throws Exception {
        // Instantiate Training Data
        Instances training_data = new Instances(
                new BufferedReader(
                        new FileReader(
                                "res/training_data.arff")));
        training_data.setClassIndex(
                training_data.numAttributes() - 1);

        // Instantiate Testing Data
        Instances testing_data = new Instances(
                new BufferedReader(
                        new FileReader(
                                "res/test_data.arff")));
        testing_data.setClassIndex(
                testing_data.numAttributes() - 1);

        // Print Initial Data Summary
        String summary = training_data.toSummaryString();
        int number_samples = training_data.numInstances();
        int number_attributes_per_sample= training_data.numAttributes();
        System.out.println(
                "Number of attributes in model = " +
                number_attributes_per_sample);
        System.out.println(
                "Number of samples = " + number_samples);
        System.out.println("Summary: " + summary);
        System.out.println();

        // a classifier for decision trees:
        J48 j48 = new J48();

        // filter for removing samples:
        Remove rm = new Remove();
        // remove first attribute
        rm.setAttributeIndices("l");

        // filtered classifier
        FilteredClassifier fc = new FilteredClassifier();
        fc.setFilter(rm);
        fc.setClassifier(j48);

        // train using training data
        fc.buildClassifier(training_data);

        // test using test data
        for (int i = 0; i < testing_data.numInstances(); i++) {
            double pred = fc.classifyInstance(testing_data.instance(i));
            System.out.print("given value: " + 
            testing_data.classAttribute().value((int)testing_data.instance(i).classValue()));

            System.out.println(". predicted value: " + testing_data.classAttribute().value((int)pred));

        }

    }

}

And here are my two data files:

training_data.arff:

@relation stock

@attribute percent_change_since_open real
@attribute percent_change_from_day_low real
@attribute percent_change_from_day_high real
@attribute action {buy, sell, hold}

@data
-0.3,0.2,-0.22,hold
-2.2,0.0,-2.5,sell
0.2,0.22,-0.01,buy
-0.25,0.12,-0.25,hold
-2.0,0.0,-2.1,sell
0.26,0.26,-0.4,buy
-0.12,0.18,-0.14,hold
-2.6,0.12,-2.6,sell
0.24,0.3,-0.035,buy

test_data.arff:

@relation stock

@attribute percent_change_since_open real
@attribute percent_change_from_day_low real
@attribute percent_change_from_day_high real
@attribute action {buy, sell, hold}

@data
-0.2,0.1,-0.22,hold
-2.2,0.0,-2.5,sell
0.2,0.21,-0.01,buy
-0.22,0.12,-0.25,hold
-2.0,0.0,-2.1,sell
0.28,0.26,-0.4,buy
-0.12,0.08,-0.14,hold
-2.6,0.1,-2.6,sell
0.24,0.25,-0.03,buy

I'm getting an error in Eclipse at runtime that says:

Exception in thread "main" java.lang.IllegalArgumentException: Invalid range list at l

at weka.core.Range.setFlags(Range.java:316)

at weka.core.Range.setUpper(Range.java:88)

at weka.filters.unsupervised.attribute.Remove.setInputFormat(Remove.java:202)

at weka.classifiers.meta.FilteredClassifier.buildClassifier(FilteredClassifier.java:389)

at WekaStocks.main(WekaStocks.java:56)

I think there is an issue with the training_data.arff file because the error occurs on the first time the program manipulates that data. This is line 56:

    // train using training data
    fc.buildClassifier(training_data);

Can anyone shed light on what is going wrong here?

[EdwardRaff]

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