Package eu.admire.gridminer.client.toolkit.activity.dt.training

Examples of eu.admire.gridminer.client.toolkit.activity.dt.training.SprintClassifier

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            service = args[0];
        }
        SQLQuery query = new SQLQuery();
        query.setResourceID("MySQLResource");
        query.addExpression("SELECT temperature, humidity, outlook, windy, weather.play FROM weather JOIN measurements ON weather.id = measurements.id");
        SprintClassifier classifier = new SprintClassifier();
        classifier.addClassName("play");
        classifier.addClassValues(new String[] {"yes", "no"});
        classifier.connectDataInput(query.getDataOutput());
        Evaluate evaluate = new Evaluate();
        evaluate.connectPMMLTreeInput(classifier.getResultOutput());
        evaluate.connectDataInput(query.getDataOutput());
        DeliverToRequestStatus deliverDT = new DeliverToRequestStatus();
        deliverDT.connectInput(classifier.getResultOutput());
        DeliverToRequestStatus deliverEval = new DeliverToRequestStatus();
        deliverEval.connectInput(evaluate.getResultOutput());
        PipelineWorkflow workflow = new PipelineWorkflow();
        workflow.add(query);
        workflow.add(classifier);
        workflow.add(evaluate);
        workflow.add(deliverDT);
        workflow.add(deliverEval);
               
        new Execute(service).execute(workflow);
           
        System.out.println("   ---- Decision tree:  ----  ");
        System.out.println(classifier.nextResult());
        System.out.println("\n\n  ---- Evaluation result:  ----  ");
        System.out.println(evaluate.nextResult());
       
    }
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        join.addColumnIds2(0);
        join.connectData1Input(query1.getDataOutput());
        join.connectData2Input(query2.getDataOutput());
        join.addProjectColumnIds1(new int[] {1,2,3});
        join.addProjectColumnIds2(new int[] {1,2});
        SprintClassifier classifier = new SprintClassifier();
        classifier.addClassName("play");
        classifier.addClassValues(new String[] {"yes", "no"});
        classifier.connectDataInput(join.getResultOutput());
        DeliverToRequestStatus deliverDT = new DeliverToRequestStatus();
        deliverDT.connectInput(classifier.getResultOutput());
        Evaluate evaluate = new Evaluate();
        evaluate.connectPMMLTreeInput(classifier.getResultOutput());
        evaluate.connectDataInput(join.getResultOutput());
        DeliverToRequestStatus deliver = new DeliverToRequestStatus();
        deliver.connectInput(evaluate.getResultOutput());
       
        PipelineWorkflow workflow = new PipelineWorkflow();
        workflow.add(query1);
        workflow.add(query2);
        workflow.add(join);
        workflow.add(classifier);
        workflow.add(deliverDT);
        workflow.add(evaluate);
        workflow.add(deliver);
       
        new Execute(service).execute(workflow);
        System.out.println("   ---- Decision tree:  ----  ");
        System.out.println(classifier.nextResult());
        System.out.println("\n\n  ---- Evaluation result:  ----  ");
        System.out.println(evaluate.nextResult());
    }
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            {
                union[i].connectDataInput(j-1, split.getOutput(j));
            }
            workflow.add(union[i]);
           
            classifier[i] = new SprintClassifier();
            classifier[i].addClassName("play");
            classifier[i].addClassValues(new String[] {"yes", "no"});
            classifier[i].connectDataInput(union[i].getDataOutput());
           
            DeliverToRequestStatus deliverDT = new DeliverToRequestStatus();
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Related Classes of eu.admire.gridminer.client.toolkit.activity.dt.training.SprintClassifier

  • eu.admire.ogsadai.scenario.CrossValidationScenario
  • eu.admire.ogsadai.scenario.DataMiningEvaluationScenario
  • eu.admire.ogsadai.scenario.DataMiningJoinedData
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