Java tutorial
/* Copyright 2015 Barcelona Supercomputing Center Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ package es.bsc.autonomic.powermodeller.tools.classifiers; import es.bsc.autonomic.powermodeller.DataSet; import es.bsc.autonomic.powermodeller.exceptions.WekaWrapperException; import weka.classifiers.Classifier; import weka.core.Instances; import weka.core.converters.ConverterUtils; public class LinearRegressionClassifier extends WekaWrapper { @Override public Classifier buildClassifier(DataSet training_ds) { logger.debug("Building LinearRegression classifier."); Classifier model; // Get the independent variable index String independent = training_ds.getIndependent(); if (independent == null) throw new WekaWrapperException("Independent variable is not set in dataset."); try { // Read all the instances in the file (ARFF, CSV, XRFF, ...) ConverterUtils.DataSource source = new ConverterUtils.DataSource(training_ds.getFilePath()); Instances instances = source.getDataSet(); // Set the independent variable (powerWatts). instances.setClassIndex(instances.attribute(independent).index()); // Builds a regression model for the given data. model = new weka.classifiers.functions.LinearRegression(); // Build Linear Regression model.buildClassifier(instances); } catch (WekaWrapperException e) { logger.error("Error while creating Linear Regression classifier.", e); throw new WekaWrapperException("Error while creating Linear Regression classifier."); } catch (Exception e) { logger.error("Error while applying Linear Regression to data set instances.", e); throw new WekaWrapperException("Error while applying Linear Regression to data set instances."); } return model; } }