Examples of printHeader()


Examples of net.sf.flatpack.writer.Writer.printHeader()

        Map<String, Object> firstRow = data.get(0);

        Writer writer = createWriter(exchange, firstRow, stream);
        try {
            boolean first = true;
            writer.printHeader();
            for (Map<String, Object> row : data) {
                if (ignoreFirstRecord && first) {
                    // skip first row
                    first = false;
                    continue;
View Full Code Here

Examples of net.sf.flatpack.writer.Writer.printHeader()

        Map<String, Object> firstRow = data.get(0);

        Writer writer = createWriter(exchange, firstRow, stream);
        try {
            boolean first = true;
            writer.printHeader();
            for (Map<String, Object> row : data) {
                if (ignoreFirstRecord && first) {
                    // skip first row
                    first = false;
                    continue;
View Full Code Here

Examples of net.sf.flatpack.writer.Writer.printHeader()

        Map<String, Object> firstRow = data.get(0);

        Writer writer = createWriter(exchange, firstRow, stream);
        try {
            boolean first = true;
            writer.printHeader();
            for (Map<String, Object> row : data) {
                if (ignoreFirstRecord && first) {
                    // skip first row
                    first = false;
                    continue;
View Full Code Here

Examples of weka.classifiers.evaluation.output.prediction.AbstractOutput.printHeader()

    AbstractOutput classificationOutput = null;
    if (forPredictionsPrinting.length > 0) {
      // print the header first
      classificationOutput = (AbstractOutput) forPredictionsPrinting[0];
      classificationOutput.setHeader(data);
      classificationOutput.printHeader();
    }

    // Do the folds
    for (int i = 0; i < numFolds; i++) {
      Instances train = data.trainCV(numFolds, i, random);
View Full Code Here

Examples of weka.classifiers.evaluation.output.prediction.AbstractOutput.printHeader()

    AbstractOutput classificationOutput = null;
    if (forPredictionsPrinting.length > 0) {
      // print the header first
      classificationOutput = (AbstractOutput) forPredictionsPrinting[0];
      classificationOutput.setHeader(data);
      classificationOutput.printHeader();
    }

    // Do the folds
    for (int i = 0; i < numFolds; i++) {
      Instances train = data.trainCV(numFolds, i, random);
View Full Code Here
TOP
Copyright © 2018 www.massapi.com. All rights reserved.
All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.