e8511041a942b968fa5ebae67228b39d9db11de1,src/main/java/com/datumbox/examples/DataModeling.java,DataModeling,main,#String[]#,47

Before Change


        
        //Fit the modeler
        //---------------
        Modeler modeler = new Modeler("LaborStatistics", conf);
        modeler.fit(trainingDataframe, trainingParameters);
        
        
        
        //Use the modeler
        //---------------
        
        //Get validation metrics on the training set
        ValidationMetrics vm = modeler.validate(trainingDataframe);
        modeler.setValidationMetrics(vm); //store them in the model for future reference
        
        //Predict a new Dataframe
        modeler.predict(testingDataframe);

After Change


        
        //Setup Training Parameters
        //-------------------------
        Modeler.TrainingParameters trainingParameters = new Modeler.TrainingParameters();
        
        //Model Configuration
        trainingParameters.setModelerTrainingParameters(new NLMS.TrainingParameters());

        //Set data transfomation configuration
        trainingParameters.setDataTransformerTrainingParameters(new DummyXYMinMaxNormalizer.TrainingParameters());
        
        //Set feature selection configuration
        trainingParameters.setFeatureSelectorTrainingParameters(null);
        
        
        
        //Fit the modeler
        //---------------
        Modeler modeler = MLBuilder.create(trainingParameters, conf);
        modeler.fit(trainingDataframe);
        modeler.save("LaborStatistics");

        
        //Use the modeler
        //---------------

        //Make predictions on the training set
        modeler.predict(trainingDataframe);

        //Get validation metrics on the training set
        LinearRegressionMetrics vm = new LinearRegressionMetrics(trainingDataframe);
        
        //Predict a new Dataframe
        modeler.predict(testingDataframe);