Example usage for weka.filters.unsupervised.attribute NominalToBinary setInputFormat

Introduction

In this page you can find the example usage for weka.filters.unsupervised.attribute NominalToBinary setInputFormat.

Prototype

@Override
public boolean setInputFormat(Instances instanceInfo) throws Exception 

Source Link

Document

Sets the format of the input instances.

Usage

From source file:ffnn.FFNN.java

public static Instances preprocess(Instances i) {
    try {/*w  w w . j a v a 2  s .c o m*/
        Reorder rfilter = new Reorder();
        int classIdx = i.classIndex() + 1;
        String order;
        if (classIdx != 1) {
            order = "1";
            for (int j = 2; j <= i.numAttributes(); j++) {
                if (j != classIdx) {
                    order = order + "," + j;
                }
            }
        } else {
            order = "2";
            for (int j = 3; j <= i.numAttributes(); j++) {
                order = order + "," + j;
            }
        }
        order = order + "," + classIdx;
        rfilter.setAttributeIndices(order);
        rfilter.setInputFormat(i);
        i = Filter.useFilter(i, rfilter);

        StringToNominal stnfilter = new StringToNominal();
        stnfilter.setAttributeRange("first-last");
        stnfilter.setInputFormat(i);
        i = Filter.useFilter(i, stnfilter);

        NominalToBinary ntbfilter = new NominalToBinary();
        ntbfilter.setInputFormat(i);
        i = Filter.useFilter(i, ntbfilter);

        Normalize nfilter = new Normalize();
        nfilter.setInputFormat(i);
        i = Filter.useFilter(i, nfilter);
    } catch (Exception e) {
        System.out.println(e.toString());
    }
    return i;
}

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From source file:ffnn.FFNNTubesAI.java

public static Instance filterNominalNumeric(Instance i) throws Exception {
    NominalToBinary filter = new NominalToBinary();
    filter.setInputFormat(i.dataset());
    filter.input(i);// www.  j  a  v  a  2  s  .c om
    return filter.output();
}

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From source file:ffnn.FFNNTubesAI.java

public static Instances filterNominalNumeric(Instances i) {
    NominalToBinary filter = new NominalToBinary();
    Instances temp_instances = new Instances(i);
    if (temp_instances.classIndex() > -1) { //Jika ada classs index
        temp_instances.setClassIndex(-1); //Unset
    }/* www  .java 2  s.  c o  m*/
    try {
        filter.setInputFormat(temp_instances);
        temp_instances = Filter.useFilter(temp_instances, filter);
    } catch (Exception ex) {
        Logger.getLogger(FFNN.class.getName()).log(Level.SEVERE, null, ex);
    }
    return temp_instances;
}

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From source file:liac.igmn.loader.DataLoader.java

License:Open Source License

/**
 * Carrega dataset a partir de arquivo ARFF e binariza os atributos nominais.
 * Assume que a classe seja o ultimo atributo.
 * //from  w w w. j a va 2 s.co m
 * @param filename path do arquivo
 * @return dataset
 * @throws DataLoaderException lancado quando o arquivo nao e encontrado
 * ou quando ocorre algum erro de IO
 */
public static Dataset loadARFF(String filename) throws DataLoaderException {
    Dataset dataset = new Dataset();
    try {
        ArffLoader loader = new ArffLoader();

        loader.setSource(new File(filename));
        Instances data = loader.getDataSet();
        Instances m_Intances = new Instances(data);

        data.setClassIndex(data.numAttributes() - 1);

        String[] classes = new String[data.numClasses()];
        for (int i = 0; i < data.numClasses(); i++)
            classes[i] = data.classAttribute().value(i);
        dataset.setClassesNames(classes);

        NominalToBinary filter = new NominalToBinary();
        filter.setInputFormat(m_Intances);
        filter.setOptions(new String[] { "-A" });
        m_Intances = Filter.useFilter(m_Intances, filter);

        int inputSize = m_Intances.numAttributes() - data.numClasses();

        dataset.setInputSize(inputSize);
        dataset.setNumClasses(data.numClasses());

        dataset.setWekaDataset(m_Intances);
    } catch (IOException e) {
        throw new DataLoaderException("Arquivo no encontrado", e.getCause());
    } catch (Exception e) {
        throw new DataLoaderException("Falha na converso do arquivo", e.getCause());
    }

    return dataset;
}

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From source file:liac.preprocessing.DatasetFilter.java

License:Open Source License

public static Dataset nominalToBinary(Dataset dataset) throws Exception {
    Instances instances = dataset.getWekaDataset();
    NominalToBinary filter = new NominalToBinary();
    filter.setInputFormat(instances);
    instances = Filter.useFilter(instances, filter);
    dataset.setWekaDataset(instances);//from   ww w.j a  v  a  2s  .  c  om

    return dataset;
}

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