Package org.dmg.pmml31.NumericInfoDocument

Examples of org.dmg.pmml31.NumericInfoDocument.NumericInfo

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    {
        PMMLDocument result = PMMLDocument.Factory.newInstance();
        PMML pmmlObject = result.addNewPMML();
        pmmlObject.setVersion("3.0");
        // head of PMML document
        Header header = pmmlObject.addNewHeader();
        header.setCopyright("www.gridminer.org");
        Application application = header.addNewApplication();
        application.setName("GridMiner");
        application.setVersion("1.0");
        //data dictionary
        DataDictionary dataDictionary = pmmlObject.addNewDataDictionary();
        BigInteger pom = new BigInteger(String.valueOf(columnCount));
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        }       
        pmmlObject.setDataDictionary(mPMML.getDataDictionary());
        pmmlObject.getDataDictionary().setDataFieldArray(dataFields);
               
        //ModelStat
        MiningModel miningModel = pmmlObject.addNewMiningModel();
        miningModel.setModelName("Statistica");
        org.dmg.pmml31.ModelStatsDocument.ModelStats modelStats =
            miningModel.addNewModelStats();
       
        for(int i=0; i<columnCount; i++)
        {
            UnivariateStats statfield = modelStats.addNewUnivariateStats();
            statfield.setField(colInfo[i].getName());
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            // all attribute are continuous in this phase
            dataField.setOptype(OPTYPE.CONTINUOUS);        
        }
       
        //ModelStat
        MiningModel miningModel = pmmlObject.addNewMiningModel();
        miningModel.setModelName("Statistica");
        org.dmg.pmml31.ModelStatsDocument.ModelStats modelStats =
            miningModel.addNewModelStats();
       
        for (int i=0; i<columnCount; i++)
        {
            UnivariateStats statfield = modelStats.addNewUnivariateStats();
            statfield.setField(colInfo[i].getName());
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                histogram_values[i] = new ArrayList(distinctValue[i]);
            }
            else { //continuous and ordinal type  
                if (interval[i]!=null)
                {
                    NumericInfo numericInfo = stats[i].getNumericInfo();
                    // we recount this values
                    minimum[i] = Double.POSITIVE_INFINITY;
                    maximum[i] = Double.NEGATIVE_INFINITY;               
                    sum[i] = 0.0;               
                    sum2[i] = 0.0;
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            }
            else
            { 
                if (interval[i]!=null)
                {
                    NumericInfo numInfo = statfield.addNewNumericInfo();
                    numInfo.setMinimum(minimum[i]);
                    numInfo.setMaximum(maximum[i]);
                    numInfo.setMean(mean[i]);
                    numInfo.setStandardDeviation(stddev[i]);               
                   
                    // ContStats                                                               
                    ContStats contsStats = statfield.addNewContStats();
                    contsStats.setTotalValuesSum(sum[i]);
                    contsStats.setTotalSquaresSum(sum2[i]);  
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        List actual = output.getActualBlocks();
        assertEquals(1, actual.size());
        PMMLDocument pmml = (PMMLDocument)actual.get(0);
       
        NumericInfo info = pmml.getPMML().getMiningModelArray(0).getModelStats().getUnivariateStatsArray(0).getNumericInfo();
        assertEquals(0, Double.compare(10, info.getMinimum()));
        assertEquals(0, Double.compare(20, info.getMean()));
        assertEquals(0, Double.compare(30, info.getMaximum()));
       
       
    }
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            if (colType.equalsIgnoreCase("integer")||
                colType.equalsIgnoreCase("float")||
                colType.equalsIgnoreCase("double"))
            {
               // numeric info
                NumericInfo numInfo = statfield.addNewNumericInfo();
                numInfo.setMinimum(minimum[i]);
                numInfo.setMaximum(maximum[i]);
                numInfo.setMean(mean[i]);
                numInfo.setStandardDeviation(stddev[i]);
            }
        }
        return result;
    }
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        }
    }
   
    public PMMLDocument toObject()
    {
        PMMLDocument result = PMMLDocument.Factory.newInstance();
        PMML pmmlObject = result.addNewPMML();
        pmmlObject.setVersion("3.0");
        //head of PMML document
        pmmlObject.setHeader(mPMML.getHeader());
        //data dictionary
        DataField[] dataFields = mPMML.getDataDictionary().getDataFieldArray();
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        activity.process();
       
        List actual = output.getActualBlocks();
        assertEquals(1, actual.size());
        PMMLDocument pmml = (PMMLDocument)actual.get(0);
       
        NumericInfo info = pmml.getPMML().getMiningModelArray(0).getModelStats().getUnivariateStatsArray(0).getNumericInfo();
        assertEquals(0, Double.compare(10, info.getMinimum()));
        assertEquals(0, Double.compare(20, info.getMean()));
        assertEquals(0, Double.compare(30, info.getMaximum()));
       
       
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        activity.process();
       
        List actual = output.getActualBlocks();
        assertEquals(1, actual.size());
        PMMLDocument pmml = (PMMLDocument)actual.get(0);
       
        PMMLToXMLCharArraysActivity toXML = new PMMLToXMLCharArraysActivity();
        input = new MockInputPipe(pmml);
        toXML.addInput("pmml", input);
       
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Related Classes of org.dmg.pmml31.NumericInfoDocument.NumericInfo

  • eu.admire.gridminer.datapreprocessing.statistic.ModelStats
  • eu.admire.gridminer.datapreprocessing.statistic.ModelStatsInterval
  • eu.admire.ogsadai.activity.datapreprocessing.AdvStatisticsActivity
  • eu.admire.ogsadai.activity.datapreprocessing.DPPMethodsActivity
  • eu.admire.ogsadai.activity.datapreprocessing.PMMLToXMLCharArraysActivity
  • eu.admire.ogsadai.activity.datapreprocessing.StatisticsActivityTest
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