cobwebxubasedalgorithm.java

一个数据挖掘软件ALPHAMINERR的整个过程的JAVA版源代码

package com.prudsys.pdm.Models.Clustering.CDBased;

import com.prudsys.pdm.Core.*;
import com.prudsys.pdm.Input.*;
import com.prudsys.pdm.Transform.*;
import com.prudsys.pdm.Transform.Special.*;
import com.prudsys.pdm.Models.Clustering.*;

public abstract class CobwebXubasedAlgorithm extends ClusteringAlgorithm{

	public CobwebXubasedAlgorithm()
	{}
    public MiningSettings createMiningSettings() {

        return new CobwebXubasedSettings();
      }

    public MiningModel buildModel() throws MiningException
    {
        long start = ( new java.util.Date() ).getTime();

        // Outlier treatment and missing value replacement:
        TreatOutlierValueStream tro   = new TreatOutlierValueStream(miningInputStream);
        tro.setNumOutliers( ApplicationAttribute.OUTLIER_TREATMENT_METHOD_asExtremeValues );
        tro.createTreatOutlierValueTransformationStep();

        ReplaceMissingValueStream rep = new ReplaceMissingValueStream(miningInputStream);
        miningInputStream             = new MiningArrayStream( rep.createReplaceMissingValueStream() );

        // Run algorithm:
        runAlgorithm();

        // Transform unbounded -> bounded categorical attributes (e.g. for PMML):
        metaData.getMetaDataOp().unboundedToBoundedCategories();

        // Create cluster model:
        CDBasedClusteringMiningModel model = new CDBasedClusteringMiningModel();
        model.setMiningSettings( miningSettings );
        model.setInputSpec( applicationInputSpecification );

        // Outlier treatment and missing value in application input specification:
        // Create inner transformation object:
        MiningTransformationActivity mta = new MiningTransformationActivity();
        mta.addTransformationStep( tro.getMts() );
        mta.addTransformationStep( rep.getMts() );
        model.setMiningTransform( mta );

        // Outliers and missing values in application input specification:
        applicationInputSpecification.setInputSpecFromInnerTrafo(metaData, tro, rep);

        // Set clusters and distance type:
        //model.setClusters( getClusters() );
        //model.setDistance( distance );

        // Set cluster model:
        this.miningModel = model;

        long end = ( new java.util.Date() ).getTime();
        timeSpentToBuildModel = ( end - start ) / 1000.0;

        return model;
    }

	
    
}