List of toSummaryString() Examples

Examples of toSummaryString()

org.integratedmodelling.riskwiz.learning.data.Instances.toSummaryString()
Generates a string summarizing the set of instances. Gives a breakdown for each attribute indicating the number of missing/discrete/unique values and other information. @return a string summarizing the dataset
weka.classifiers.Evaluation.toSummaryString()
Calls toSummaryString() with no title and no complexity stats. @return a summary description of the classifier evaluation
weka.classifiers.timeseries.eval.TSEvaluation.toSummaryString()
Generates a String containing the results of evaluating the forecaster. @return a String containing the results of evaluating the forecaster @throws Exception if a problem occurs
weka.core.Instances.toSummaryString()
Generates a string summarizing the set of instances. Gives a breakdown for each attribute indicating the number of missing/discrete/unique values and other information. @return a string summarizing the dataset

Examples of weka.classifiers.Evaluation.toSummaryString()

        output.getBuffer().toString());
      
      // Output meta information
      sb = new StringBuilder();
      sb.append(classifier.toString() + LF);
      sb.append(eval.toSummaryString() + LF);
      sb.append(eval.toMatrixString() + LF);
      
      FileUtils.writeStringToFile(
        new File(OUTPUT_DIR + "/" + testDataset.toString() + "/" + wekaClassifier.toString() + "/" + testDataset.toString() + ".meta.txt"),
        sb.toString());

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Examples of weka.classifiers.Evaluation.toSummaryString()

            predictedData = new Instances(pred, 0);
          for (int j = 0; j < pred.numInstances(); j++)
            predictedData.add(pred.instance(j));            
      }
      
      System.out.println(eval.toSummaryString());
      System.out.println(eval.toMatrixString());
      
      // Prepare output scores
      String[] scores = new String[predictedData.numInstances()];

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Examples of weka.classifiers.Evaluation.toSummaryString()

        predictedData);
      
      // Output meta information
      sb = new StringBuilder();
      sb.append(baseClassifier.toString() + LF);
      sb.append(eval.toSummaryString() + LF);
      sb.append(eval.toMatrixString() + LF);
      
      FileUtils.writeStringToFile(
        new File(OUTPUT_DIR + "/" + dataset.toString() + "/" + wekaClassifier.toString() + "/" + dataset.toString() + ".meta.txt"),
        sb.toString());

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Examples of weka.classifiers.Evaluation.toSummaryString()

    if(canMeasureCPUTime)
      testCPUTimeElapsed = thMonitor.getThreadUserTime(thID) - CPUStartTime;
    testTimeElapsed = System.currentTimeMillis() - testTimeStart;
    thMonitor = null;
    
    m_result = eval.toSummaryString();
    // The results stored are all per instance -- can be multiplied by the
    // number of instances to get absolute numbers
    int current = 0;
    result[current++] = new Double(train.numInstances());
    result[current++] = new Double(eval.numInstances());

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Examples of weka.classifiers.Evaluation.toSummaryString()

    if(canMeasureCPUTime)
      testCPUTimeElapsed = thMonitor.getThreadUserTime(thID) - CPUStartTime;
    testTimeElapsed = System.currentTimeMillis() - testTimeStart;
    thMonitor = null;
    
    m_result = eval.toSummaryString();
    // The results stored are all per instance -- can be multiplied by the
    // number of instances to get absolute numbers
    int current = 0;
    result[current++] = new Double(train.numInstances());
    result[current++] = new Double(eval.numInstances());

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Examples of weka.classifiers.Evaluation.toSummaryString()

        default:
        throw new Exception("Test mode not implemented");
      }
      
      if (outputSummary) {
        outBuff.append(eval.toSummaryString(outputEntropy) + "\n");
      }


      if (inst.attribute(classIndex).isNominal()) {


        if (outputPerClass) {

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Examples of weka.classifiers.Evaluation.toSummaryString()

              if (outputPredictionsText && classificationOutput.generatesOutput()) {
                outBuff.append("\n");
              } 
      
              if (outputSummary) {
                outBuff.append(eval.toSummaryString(outputEntropy) + "\n");
              }
      
              if (userTestStructure.classAttribute().isNominal()) {
  
                if (outputPerClass) {

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Examples of weka.classifiers.Evaluation.toSummaryString()

    if(canMeasureCPUTime)
      testCPUTimeElapsed = thMonitor.getThreadUserTime(thID) - CPUStartTime;
    testTimeElapsed = System.currentTimeMillis() - testTimeStart;
    thMonitor = null;
    
    m_result = eval.toSummaryString();
    // The results stored are all per instance -- can be multiplied by the
    // number of instances to get absolute numbers
    int current = 0;
    result[current++] = new Double(train.numInstances());
    result[current++] = new Double(eval.numInstances());

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Examples of weka.classifiers.Evaluation.toSummaryString()

      filteredClassifier.buildClassifier(train);
      
      Evaluation eval = new Evaluation(train);
          eval.evaluateModel(filteredClassifier, test);
          
          System.out.println(eval.toSummaryString());
        System.out.println(eval.toMatrixString());
    }
    catch (Exception e) {
      throw new SimilarityException(e);
    }

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Examples of weka.classifiers.timeseries.eval.TSEvaluation.toSummaryString()

          m_history.updateResult(name);
        }


        // evaluation summary
        if (eval.getEvaluateOnTrainingData() || eval.getEvaluateOnTestData()) {
          outBuff.append("\n" + eval.toSummaryString());
          m_history.updateResult(name);
        }


        // result object list
        List<Object> resultList = (m_configAndBuild)

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