8 Converting to the ODM 10.2 Java API

Connect to the DMS

Connect to the DMS

//Create a DMS object
DataMiningServer m_dms =  new DataMiningServer  
  ( "put DB URL here",  //JDBC URL
    "user name",        //User Name
    "password"          //Password
  );
//Login to the DMS and create a DMS Connection 
m_dmsConn = m_dms.login();

//Create ConnectionFactory & connection
OraConnectionFactory m_dmeConnFactory =  
  new OraConnectionFactory();
ConnectionSpec connSpec =  
  m_dmeConnFactory.getConnectionSpec();
connSpec.setURI( "put DB URL here" );
connSpec.setName( "user name" ); 
connSpec.setPassword( "password" );
m_dmeConn =   
  m_dmeConnFactory.getConnection( connSpec );

Create a PhysicalDataSpecification

Create and Save PhysicalDataSet

LocationAccessData lad =  new LocationAccessData
  ( "MINING_DATA_BUILD_V",   //Table/view Name
    "DMUSER"                 //Schema Name
  );
PhysicalDataSpecification pds =
  newNonTransactionalDataSpecification  (lad);

PhysicalDataSetFactory pdsFactory =
  ( PhysicalDataSetFactory )m_dmeConn.getFactory
  ( "javax.datamining.data.PhysicalDataSet" );
m_paFactory = ( PhysicalAttributeFactory )
  m_dmeConn.getFactory
  ( "javax.datamining.data.PhysicalAttribute" );
PhysicalDataSet buildData = m_pdsFactory.create
  ( "MINING_DATA_BUILD_V",false );
PhysicalAttribute pa =m_paFactory.create
  ( "cust_id", AttributeDataType.integerType,
  PhysicalAttributeRole.caseId );
buildData.addAttribute( pa );
m_dmeConn.saveObject( "nbBuildData", buildData, true );

Create and Save MiningFunctionSettings

Create BuildSettings

NaiveBayesSettings nbAlgo =
  new NaiveBayesSettings (0.01f, 0.01f);
ClassificationFunctionSettings mfs =
  ClassificationFunctionSettings.create
  ( m_dmsConn,          //DMS Connection
    nbAlgo,             //NB algorithm settings
    pds,                //Build data specification
   "AFFINITY_CARD",     //Target column
    AttributeType.categorical,   //Attribute type
    DataPreparationStatus.unprepared
  );
//Set Cust_ID attribute as inactive 
mfs.adjustAttributeUsage( new String[]{"CUST_ID"},
  AttributeUsage.inactive );
mfs.store( m_dmsConn,"NBDemo_MFS" );

m_clasFactory = ( ClassificationSettingsFactory )
  m_dmeConn.getFactory
  ( "javax.datamining.supervised.classification.
   ClassificationSettings" );
m_nbFactory = ( NaiveBayesSettingsFactory )
  m_dmeConn.getFactory
  ("javax.datamining.algorithm.naivebayes.
   NaiveBayesSettings");
//Create NB algorithm settings
NaiveBayesSettings nbAlgo = m_nbFactory.create();
nbAlgo.setPairwiseThreshold( 0.01f );
nbAlgo.setSingletonThreshold( 0.01f );
//Create ClassificationSettings
ClassificationSettings buildSettings = 
  m_clasFactory.create();
buildSettings.setAlgorithmSettings(nbAlgo);
buildSettings.setTargetAttributeName
  ( "affinity_card");
m_dmeConn.saveObject
  ("nbBuildSettings",buildSettings,true);

Create and Execute MiningBuildTask

Create and Execute BuildTask

MiningBuildTask buildTask =  
  new MiningBuildTask
  ( pds,            //Build data specification
   "NBDemo_MFS",    //Mining function settings
   "NBDemo_Model"   //Mining model name 
  );
//Store the taskbuild
buildTask.store( m_dmsConn,"NBDemoBuildTask" );
Task.execute( m_dmsConn );
//Wait for completion of the task
MiningTaskStatus taskStatus =
  buildTask.waitForCompletion( m_dmsConn );

m_buildFactory = ( BuildTaskFactory )
  m_dmeConn.getFactory
  ( "javax.datamining.task.BuildTask" );
BuildTask buildTask = m_buildFactory.create
  ( "nbBuildData",     //Build data specification
    "nbBuildSettings", //build settings name
    "nbModel"          //Mining model namem_dme
  );
Conn.saveObject( "nbBuildTask", taskObj, true );
ExecutionHandle execHandle = 
  m_dmeConn.execute( taskName );
ExecutionStatus status =
  execHandle.waitForCompletion(
Integer.MAX_VALUE);

Retrieve MiningModel

Retrieve Model

NaivebayesModel model =  ( NaiveBayesModel )
  SupervisedModel.restore
  ( m_dmeConn, "NBDemo_Model" );

ClassificationModel model =  ( ClassificationModel )
  m_dmeConn.retrieveObject
  ( "nbModel", NamedObject.model );

Evaluate the Model

Evaluate the Model

//Compute accuracy & confusionmatrix
LocationAccessData lad = new LocationAccessData
  ( "MINING_DATA_TEST_V", "DMUSER" ); //Schema Name
PhysicalDataSpecification pds =
  new NonTransactionalDataSpecification( lad );
ClassificationTestTask testTask =
  new ClassificationTestTask ( pds,"NBDemo_Model", 
  "NBDemo_TestResults" );
testTask.store( m_dmsConn, "NBDemoTestTask" );
testTask.execute( m_dmsConn );
MiningTaskStatus taskStatus =
  testTask.waitForCompletion( m_dmsConn );
ClassificationTestResult testResult =
  ClassificationTestResult.restore
  ( m_dmsConn, "NBDemo_TestResults" );
float accuracy = testResult.getAccuracy();
CategoryMatrix confusionMatrix =
  TestResult.getConfusionMatrix();
//Compute lift
Category positiveCategory = new Category
  ( "Positive value", "1",DataType.intType );
MiningLiftTask liftTask =
  new MiningLiftTask  
  ( pds, 
    10,           //Number of quantiles to be used
    positiveCategory,    /positive target value  
   "NBDemo_Model",       // model to be tested  
   "NBDemo_LiftResults"  //Lift results name
  );
liftTask.store( m_dmsConn, "NBDemoLiftTask" );
liftTask.execute( m_dmsConn );
MiningTaskStatus taskStatus =
  liftTask.waitForCompletion( m_dmsConn );
MiningLiftResult liftResult =
  MiningLiftResult.restore
 ( m_dmsConn,"NBDemo_LiftResults" );

//Compute accuracy, confusion matrix, lift & roc
PhysicalDataSet testData = m_pdsFactory.create
  ( "MINING_DATA_TEST_V", false );
PhysicalAttribute pa = m_paFactory.create
  ( "cust_id", AttributeDataType.integerType,
    PhysicalAttributeRole.caseId );
testData.addAttribute( pa );
m_dmeConn.saveObject
  ( "nbTestData", testData, true );
ClassificationTestTask testTask = m_testFactory.create
  ( "nbTestData", "nbModel", "nbTestMetrics" );
testTask.setNumberOfLiftQuantiles( 10 );
testTask.setPositiveTargetValue( new Integer(1) );
m_dmeConn.saveObject( "nbTestTask", testTask, true );
ExecutionHandle execHandle = 
  m_dmeConn.execute("nbTestTask");
ExecutionStatus status = execHandle.waitForCompletion
  ( Integer.MAX_VALUE );
ClassificationTestMetrics testMetrics = 
  ( ClassificationTestMetrics )
  m_dmeConn.retrieveObject
  ( "nbTestMetrics", NamedObject.testMetrics );
Double accuracy = testMetrics.getAccuracy();
ConfusionMatrix confusionMatrix =  
   testMetrics.getConfusionMatrix();
Lift lift = testMetrics.getLift();
ReceiverOperatingCharacterics roc =
  testMetrics.getROC();

Apply the Model

Apply the Model

LocationAccessData lad = new LocationAccessData
  ( "MINING_DATA_APPLY_V", "DMUSER");
PhysicalDataSpecification pds =
  new NonTransactionalDataSpecification( lad );
MiningApplyOutput mao =
  MiningApplyOutput.createDefault();
MiningAttribute srcAttribute =  new MiningAttribute
  ( "CUST_ID", DataType.intType,
    AttributeType.notApplicable
  );
Attribute destAttribute = new Attribute
  ("CUST_ID", DataType.intType);
ApplySourceAttributeItem m_srcAttrItem =  
  new ApplySourceAttributeItem
  ( srcAttribute,destAttribute);
mao.addItem(m_srcAttrItem);
LocationAccessData outputTable =  
  new LocationAccessData
  ( "NBDemo_Apply_Output", "DMUSER");
MiningApplyTask applyTask = new MiningApplyTask
  ( pds,                 //test data specification
   "NBDemo_Model",       //Input model name   
    mao,                 //MiningApplyOutput object
    outputTable,         //Apply output table
   "NBDemo_ApplyResults"  //Apply results
  );
applyTask.store( m_dmsConn, "NBDemoApplyTask" );
applyTask.execute( m_dmsConn );
MiningTaskStatus taskStatus =
  applyTask.waitForCompletion( m_dmsConn );

PhysicalDataSet applyData = m_pdsFactory.create
  ( "MINING_DATA_APPLY_V", false );
PhysicalAttribute pa = m_paFactory.create
  ( "cust_id", 
    AttributeDataType.integerType,
    PhysicalAttributeRole.caseId
  );
applyData.addAttribute( pa );
m_dmeConn.saveObject( "nbApplyData",applyData,true );
ClassificationApplySettings clasAS = 
  m_applySettingsFactory.create();
m_dmeConn.saveObject( "nbApplySettings",clasAS,true );
DataSetApplyTask applyTask = m_dsApplyFactory.create
  ( "nbApplyData", 
    "nbModel",
    "nbApplySettings", 
    "nb_apply_output"
  );
m_dmeConn.saveObject
  ( "nbApplyTask", 
     applyTask,
     true
  );
ExecutionHandle execHandle = 
  m_dmeConn.execute( "nbApplyTask" );
ExecutionStatus status =
   execHandle.waitForCompletion( Integer.MAX_VALUE );