Example usage for weka.experiment InstanceQuery InstanceQuery

Introduction

In this page you can find the example usage for weka.experiment InstanceQuery InstanceQuery.

Prototype

public InstanceQuery() throws Exception 

Source Link

Document

Sets up the database drivers

Usage

From source file:adams.flow.transformer.WekaExperimentEvaluation.java

License:Open Source License

/**
 * Loads the experimental results./*ww w  .j a  va2s  .  c  om*/
 *
 * @param exp      the experiment to evaluate
 * @return      the results
 * @throws Exception    If reading fails.
 */
protected Instances getData(weka.experiment.Experiment exp) throws Exception {
    Instances result;
    String tmpStr;
    DatabaseResultListener dbListener;
    InstanceQuery query;

    // load experiment data
    if (exp.getResultListener() instanceof CSVResultListener) {
        try {
            result = DataSource
                    .read(((CSVResultListener) exp.getResultListener()).getOutputFile().getAbsolutePath());
        } catch (Exception e) {
            getLogger().log(Level.SEVERE, "Failed to get instances from CSV:", e);
            throw new Exception("Error reading experiment from file:\n" + e);
        }
    } else if (exp.getResultListener() instanceof DatabaseResultListener) {
        dbListener = (DatabaseResultListener) exp.getResultListener();
        try {
            tmpStr = dbListener.getResultsTableName(exp.getResultProducer());
            query = new InstanceQuery();
            query.setDatabaseURL(dbListener.getDatabaseURL());
            query.setUsername(dbListener.getUsername());
            query.setPassword(dbListener.getPassword());
            query.setDebug(dbListener.getDebug());
            query.connectToDatabase();
            result = query.retrieveInstances("SELECT * FROM " + tmpStr);
            query.disconnectFromDatabase();
        } catch (Exception e) {
            getLogger().log(Level.SEVERE, "Failed to get instances from database:", e);
            throw new Exception("Error reading experiment from database:\n" + e);
        }
    } else {
        throw new Exception(
                "Unsupported ResultListener '" + exp.getResultListener().getClass().getName() + "'!");
    }

    return result;
}

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From source file:adams.gui.visualization.instance.InstanceExplorer.java

License:Open Source License

/**
 * pops up SQL Viewer for SQL statement.
 *///  w w  w  .  j a v  a 2s . c om
public void loadDataFromDatabase() {
    InstanceQuery query;
    List<InstanceContainer> data;
    Instances dataset;
    Instance inst;
    int i;

    if (m_LoadFromDatabaseDialog == null) {
        if ((getParentFrame() != null) && (getParentFrame() instanceof JFrame))
            m_LoadFromDatabaseDialog = new SqlViewerDialog((JFrame) getParentFrame());
        else
            m_LoadFromDatabaseDialog = new SqlViewerDialog(null);
    }

    m_LoadFromDatabaseDialog.setVisible(true);
    if (m_LoadFromDatabaseDialog.getReturnValue() != JOptionPane.OK_OPTION)
        return;

    try {
        showStatus("Executing query: " + m_LoadFromDatabaseDialog.getQuery());
        query = new InstanceQuery();
        query.setDatabaseURL(m_LoadFromDatabaseDialog.getURL());
        query.setUsername(m_LoadFromDatabaseDialog.getUser());
        query.setPassword(m_LoadFromDatabaseDialog.getPassword());
        query.setQuery(m_LoadFromDatabaseDialog.getQuery());
        query.setSparseData(m_LoadFromDatabaseDialog.getGenerateSparseData());
        if (query.isConnected())
            query.disconnectFromDatabase();
        query.connectToDatabase();

        showStatus("Loading data...");
        data = new ArrayList<>();
        dataset = query.retrieveInstances();
        for (i = 0; i < dataset.numInstances(); i++) {
            inst = new Instance();
            inst.set(dataset.instance(i));
            inst.setID(dataset.relationName() + "." + i);
            data.add(getContainerManager().newContainer(inst));
            showStatus("Loading data " + (i + 1) + "/" + dataset.numInstances());
        }
        loadData(dataset, data);
    } catch (Exception e) {
        GUIHelper.showErrorMessage(this, "Failed to load data from database:\n" + Utils.throwableToString(e),
                "Database error");
    }

    showStatus("");
}

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From source file:core.classification.Classifiers.java

License:Open Source License

public void trainSC() throws Exception {
    String sql;/*  w w  w .j  a  v  a2s. c o  m*/

    // ---
    // Connect to the database
    // ---
    InstanceQuery query = new InstanceQuery();
    query.setDatabaseURL(dbase);
    query.setUsername("");
    query.setPassword("");

    // ---
    // ---
    // SCA
    // ---
    // ---

    sql = "SELECT ";
    sql += "CR.ratio, CR.class ";
    sql += "FROM Class_ratio AS CR;";

    query.setQuery(sql);
    Instances data = query.retrieveInstances();

    // ---
    // Setting options
    // ---
    String[] options = Utils.splitOptions(
            "-D -Q weka.classifiers.bayes.net.search.local.K2 -- -P 1 -S BAYES -E weka.classifiers.bayes.net.estimate.SimpleEstimator -- -A 0.5");
    SCA.setOptions(options);
    data.setClassIndex(data.numAttributes() - 1);

    // ---
    // Train the classifier
    // ---
    System.out.println("Building SCA ...");
    SCA.buildClassifier(data);
    System.out.println("Done.");

    // ---
    // Classifier evaluation
    // ---
    System.out.println("Cross-validation for SCA...");
    Evaluation eval = new Evaluation(data);
    eval.crossValidateModel(SCA, data, 10, new Random(1));
    System.out.println("Done.");
    System.out.println(eval.toSummaryString("\n Results for SCA: \n\n", false));

    // ---
    // ---
    // SCB
    // ---
    // ---

    sql = "SELECT ";
    sql += "Data.H2, Data.D2, Data.DX, ";
    sql += "Data.PARENT_CHAR AS PCLASS, ";
    sql += "Data.CLASS ";
    sql += "FROM Data ";
    sql += "WHERE (((Data.SEGERR)=0) AND (Data.PARENT_CHAR<>'0') );";

    query.setQuery(sql);
    data = query.retrieveInstances();

    // ---
    // Setting options
    // ---
    options = Utils.splitOptions("-L 0.3 -M 0.2 -N 500 -V 0 -S 0 -E 20 -H a");
    SCB.setOptions(options);
    data.setClassIndex(data.numAttributes() - 1);

    // ---
    // Train the classifier
    // ---
    System.out.println("Building SCB ...");
    SCB.buildClassifier(data);
    System.out.println("Done.");

    // ---
    // Classifier evaluation
    // ---
    System.out.println("Cross-validation for SCB...");
    eval = new Evaluation(data);
    eval.crossValidateModel(SCB, data, 10, new Random(1));
    System.out.println("Done.");
    System.out.println(eval.toSummaryString("\n Results for SCB: \n\n", false));

    // ---
    // ---
    // SCC
    // ---
    // ---

    // ----
    // SCC1
    // ----

    sql = "SELECT ";
    sql += "Data.LH, Data.LD, Data.LDX, Data.LCLASS, ";
    sql += "Data.CLASS ";
    sql += "FROM Data ";
    sql += "WHERE ( (Data.SEGERR)=0  AND ( (Data.LCLASS)<>'0' ) );";

    query.setQuery(sql);
    data = query.retrieveInstances();

    // ---
    // Setting options
    // ---
    options = Utils.splitOptions("-L 0.3 -M 0.2 -N 500 -V 0 -S 0 -E 20 -H a");
    SCC1.setOptions(options);
    data.setClassIndex(data.numAttributes() - 1);

    // ---
    // Train the classifier
    // ---
    System.out.println("Building SCC1 ...");
    SCC1.buildClassifier(data);
    System.out.println("Done.");

    // ---
    // Classifier evaluation
    // ---
    System.out.println("Cross-validation for SCC1...");
    eval = new Evaluation(data);
    eval.crossValidateModel(SCC1, data, 10, new Random(1));
    System.out.println("Done.");
    System.out.println(eval.toSummaryString("\n Results for SCC1: \n\n", false));

    // ----
    // SCC2
    // ----

    sql = "SELECT ";
    sql += "Data.EH, Data.ED, Data.EDX, Data.ECLASS, ";
    sql += "Data.CLASS ";
    sql += "FROM Data ";
    sql += "WHERE ( (Data.SEGERR)=0  AND ( (Data.ECLASS)<>'0' ) );";

    query.setQuery(sql);
    data = query.retrieveInstances();

    // ---
    // Setting options
    // ---
    //      options = Utils.splitOptions("-L 0.3 -M 0.2 -N 500 -V 0 -S 0 -E 20 -H a");
    SCC2.setOptions(options);
    data.setClassIndex(data.numAttributes() - 1);

    // ---
    // Train the classifier
    // ---
    System.out.println("Building SCC2 ...");
    SCC2.buildClassifier(data);
    System.out.println("Done.");

    // ---
    // Classifier evaluation
    // ---
    System.out.println("Cross-validation for SCC2...");
    eval = new Evaluation(data);
    eval.crossValidateModel(SCC2, data, 10, new Random(1));
    System.out.println("Done.");
    System.out.println(eval.toSummaryString("\n Results for SCC2: \n\n", false));

    // ----
    // SCC3
    // ----

    sql = "SELECT ";
    sql += "Data.SH, Data.SD, Data.SDX, Data.SCLASS, ";
    sql += "Data.CLASS ";
    sql += "FROM Data ";
    sql += "WHERE ( (Data.SEGERR)=0  AND ( (Data.SCLASS)<>'0' ) );";

    query.setQuery(sql);
    data = query.retrieveInstances();

    // ---
    // Setting options
    // ---
    //      options = Utils.splitOptions("-L 0.3 -M 0.2 -N 500 -V 0 -S 0 -E 20 -H a");
    SCC3.setOptions(options);
    data.setClassIndex(data.numAttributes() - 1);

    // ---
    // Train the classifier
    // ---
    System.out.println("Building SCC3 ...");
    SCC3.buildClassifier(data);
    System.out.println("Done.");

    // ---
    // Classifier evaluation
    // ---
    System.out.println("Cross-validation for SCC3...");
    eval = new Evaluation(data);
    eval.crossValidateModel(SCC3, data, 10, new Random(1));
    System.out.println("Done.");
    System.out.println(eval.toSummaryString("\n Results for SCC3: \n\n", false));

}

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From source file:core.classification.Classifiers.java

License:Open Source License

public void trainRC() throws Exception {
    // ---/*from ww w.j  a  v  a  2  s .  c  o m*/
    // Retrieve the instances in the database
    // ---
    InstanceQuery query = new InstanceQuery();
    query.setDatabaseURL(dbase);
    query.setUsername("");
    query.setPassword("");

    String sql = "SELECT ";
    sql += "Data.H2, Data.D2, Data.DX, ";
    sql += "Data.CLASS, Data.PARENT_CHAR AS PCLASS, ";
    sql += "Data.RELID ";
    sql += "FROM Data ";
    sql += "WHERE (((Data.SEGERR)=0) AND (Data.PARENT_CHAR<>'0') );";

    query.setQuery(sql);
    Instances data = query.retrieveInstances();

    // ---
    // Setting options
    // ---
    //      String[] options = Utils.splitOptions("-L 0.2 -M 0.2 -N 50 -V 0 -S 0 -E 20 -H 5 ");
    String[] options = Utils.splitOptions(
            "-cost-matrix \"[0.0 1.0 1.0 0.1 0.1; 1.0 0.0 1.0 0.1 0.1; 1.0 1.0 0.0 0.1 0.1; 10.0 10.0 10.0 0.0 1.0; 10.0 10.0 10.0 1.0 0.0]\" -S 1 -W weka.classifiers.functions.MultilayerPerceptron -- -L 0.2 -M 0.2 -N 500 -V 0 -S 0 -E 20 -H a");
    RC.setOptions(options);
    data.setClassIndex(data.numAttributes() - 1);

    // ---
    // Train
    // ---
    System.out.println("Building RC...");
    RC.buildClassifier(data);
    System.out.println("Done.");

    // ---
    // Evaluation
    // ---
    System.out.println("Cross-validation for RC...");
    Evaluation eval = new Evaluation(data);
    eval.crossValidateModel(RC, data, 10, new Random(1));
    System.out.println("Done.");
    System.out.println(eval.toSummaryString("\n Results for RC: \n\n", false));

}

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From source file:core.classification.Classifiers.java

License:Open Source License

public void trainYNC() throws Exception {
    // ---//from  w ww  . jav a  2  s  . com
    // Retrieve the instances in the database
    // ---
    InstanceQuery query = new InstanceQuery();
    query.setDatabaseURL(dbase);
    query.setUsername("");
    query.setPassword("");

    String sql = "SELECT ";
    sql += "YNCdata.PCLASS, YNCdata.CCLASS, YNCdata.RAREA, YNCdata.H, YNCdata.D, YNCdata.V, ";
    sql += "YNCdata.YN ";
    sql += "FROM YNCdata ";

    query.setQuery(sql);
    Instances data = query.retrieveInstances();

    // ---
    // Setting options
    // ---
    String[] options = Utils.splitOptions("-R -N 3 -Q 1 -M 30");
    YNC.setOptions(options);
    data.setClassIndex(data.numAttributes() - 1);

    // ---
    // Train
    // ---
    System.out.println("Building YC...");
    YNC.buildClassifier(data);
    System.out.println("Done.");

    // ---
    // Evaluation
    // ---
    System.out.println("Cross-validation for YNC...");
    Evaluation eval = new Evaluation(data);
    eval.crossValidateModel(YNC, data, 10, new Random(1));
    System.out.println("Done.");
    System.out.println(eval.toSummaryString("\n Results for YNC: \n\n", false));

}

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From source file:gr.uoc.nlp.opinion.analysis.suggestion.AnalyzeSuggestions.java

private Instances retriveTrainSet() {
    System.out.println("Retrieving dataset from Database..");

    InstanceQuery query;/* w w  w  .  j a v a 2s . c  o  m*/

    try {
        //initialize database, weka api
        query = new InstanceQuery();

        //set database attributes, weka apit
        query.setDatabaseURL(this.connection.getJdbcUrl());
        query.setUsername(this.connection.getUsername());
        query.setPassword(this.connection.getPassword());
        query.setQuery(this.queryTrainset());

        //retrieve trainset
        Instances data = query.retrieveInstances();
        data.setClassIndex(data.numAttributes() - 1);

        System.out.println("Done retrieving dataset from Database!");

        return data;
    } catch (Exception ex) {
        System.err.println("Abort!");
        Logger.getLogger(AnalyzeArguments.class.getName()).log(Level.SEVERE, null, ex);
    }

    return null;
}

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From source file:hurtowniedanych.FXMLController.java

public void trainAndTestKNN() throws FileNotFoundException, IOException, Exception {

    InstanceQuery instanceQuery = new InstanceQuery();
    instanceQuery.setUsername("postgres");
    instanceQuery.setPassword("szupek");
    instanceQuery.setCustomPropsFile(new File("./src/data/DatabaseUtils.props")); // Wskazanie pliku z ustawieniami dla PostgreSQL

    String query = "select ks.wydawnictwo,ks.gatunek, kl.mia-sto\n" + "from zakupy z,ksiazki ks,klienci kl\n"
            + "where ks.id_ksiazka=z.id_ksiazka and kl.id_klient=z.id_klient";

    instanceQuery.setQuery(query);//from  ww w . jav  a  2  s.co  m
    Instances data = instanceQuery.retrieveInstances();
    data.setClassIndex(data.numAttributes() - 1);

    data.randomize(new Random());
    double percent = 70.0;
    int trainSize = (int) Math.round(data.numInstances() * percent / 100);
    int testSize = data.numInstances() - trainSize;
    Instances trainData = new Instances(data, 0, trainSize);
    Instances testData = new Instances(data, trainSize, testSize);

    int lSasiadow = Integer.parseInt(textFieldKnn.getText());
    System.out.println(lSasiadow);

    IBk ibk = new IBk(lSasiadow);

    // Ustawienie odleglosci
    EuclideanDistance euclidean = new EuclideanDistance(); // euklidesowej
    ManhattanDistance manhatan = new ManhattanDistance(); // miejska  

    LinearNNSearch linearNN = new LinearNNSearch();

    if (comboboxOdleglosc.getSelectionModel().getSelectedItem().equals("Manhatan")) {
        linearNN.setDistanceFunction(manhatan);
    } else {
        linearNN.setDistanceFunction(euclidean);
    }

    ibk.setNearestNeighbourSearchAlgorithm(linearNN); // ustawienie sposobu szukania sasiadow

    // Tworzenie klasyfikatora
    ibk.buildClassifier(trainData);

    Evaluation eval = new Evaluation(trainData);
    eval.evaluateModel(ibk, testData);
    spr.setVisible(true);
    labelKnn.setVisible(true);
    labelOdleglosc.setVisible(true);
    labelKnn.setText(textFieldKnn.getText());
    labelOdleglosc.setText(comboboxOdleglosc.getSelectionModel().getSelectedItem().toString());
    spr.setText(eval.toSummaryString("Wynik:", true));
}

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From source file:newsclassifier.NewsClassifier.java

public void LoadDB() throws Exception {
    Class.forName("com.mysql.jdbc.Driver");
    InstanceQuery query = new InstanceQuery();
    query.setDatabaseURL("jdbc:mysql://localhost:3306/news_aggregator");
    query.setUsername("root");
    query.setPassword("");
    //query.setQuery("SELECT full_text,id_kelas FROM artikel NATURAL JOIN artikel_kategori_verified");
    query.setQuery(//from   w  w w. ja  va2s.  com
            "SELECT judul,full_text,label FROM artikel NATURAL JOIN artikel_kategori_verified NATURAL JOIN kategori");
    data = query.retrieveInstances();
}

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From source file:org.datahack.forecast.BayExample.java

public static void main(String[] args) {
    try {/*from  w w w . ja  v a 2s .  com*/
        // path to the Australian wine data included with the time series forecasting
        // package

        File output = File.createTempFile("tempWineData", "arff");
        output.deleteOnExit();
        String dataFileName = "sample-data/wine.arff";
        URL resource = BayExample.class.getResource("/" + dataFileName);
        FileUtils.copyURLToFile(resource, output);

        String pathToWineData = output.getPath();

        // load the wine data
        Instances wine = new Instances(new BufferedReader(new FileReader(pathToWineData)));

        InstanceQuery q = new InstanceQuery();

        // new forecaster
        WekaForecaster forecaster = new WekaForecaster();

        // set the targets we want to forecast. This method calls
        // setFieldsToLag() on the lag maker object for us
        forecaster.setFieldsToForecast("Fortified,Dry-white");

        // default underlying classifier is SMOreg (SVM) - we'll use
        // gaussian processes for regression instead
        forecaster.setBaseForecaster(new GaussianProcesses());

        forecaster.getTSLagMaker().setTimeStampField("Date"); // date time stamp
        forecaster.getTSLagMaker().setMinLag(1);
        forecaster.getTSLagMaker().setMaxLag(12); // monthly data

        // add a month of the year indicator field
        forecaster.getTSLagMaker().setAddMonthOfYear(true);

        // add a quarter of the year indicator field
        forecaster.getTSLagMaker().setAddQuarterOfYear(true);

        // build the model
        forecaster.buildForecaster(wine, System.out);

        // prime the forecaster with enough recent historical data
        // to cover up to the maximum lag. In our case, we could just supply
        // the 12 most recent historical instances, as this covers our maximum
        // lag period
        forecaster.primeForecaster(wine);

        // forecast for 12 units (months) beyond the end of the
        // training data
        List<List<NumericPrediction>> forecast = forecaster.forecast(12, System.out);

        // output the predictions. Outer list is over the steps; inner list is over
        // the targets
        for (int i = 0; i < 12; i++) {
            List<NumericPrediction> predsAtStep = forecast.get(i);
            for (int j = 0; j < 2; j++) {
                NumericPrediction predForTarget = predsAtStep.get(j);
                System.out.print("" + predForTarget.predicted() + " ");
            }
            System.out.println();
        }

        // we can continue to use the trained forecaster for further forecasting
        // by priming with the most recent historical data (as it becomes available).
        // At some stage it becomes prudent to re-build the model using current
        // historical data.

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

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From source file:wtute.engine.AnalysisEngine.java

public AnalysisEngine() throws Exception {
    attributeList = new FastVector();
    Class.forName("com.mysql.jdbc.Driver").newInstance();

    InstanceQuery query = new InstanceQuery();
    query.setUsername("root");
    query.setPassword("");
    query.setQuery("select sentence,sentence_quality from sentences");
    //data set is sparse
    query.setSparseData(true);//from w  w w.  j  av  a2 s.  co m
    data = query.retrieveInstances();
    StringToWordVector nts = new StringToWordVector();
    nts.setInputFormat(data);
    data = Filter.useFilter(data, nts);
}

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