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);