![]() default underlying classifier is SMOreg (SVM) – we’ll use setFieldsToLag() on the lag maker object for usįtFieldsToForecast(“Fortified,Dry-white”) WekaForecaster forecaster = new WekaForecaster() Instances wine = new Instances(new BufferedReader(new FileReader(pathToWineData))) PathToWineData = “C:\\Users\\vikas\\Desktop\\temp\\wine.arff” path to the Australian wine data included with the time series forecasting * jfreechart-1.0.13.jar (from the time series package lib directory) * jcommon-1.0.14.jar (from the time series package lib directory) * pdm-timeseriesforecasting-ce-TRUNK-SNAPSHOT.jar (from the time series package) ![]() * run the CLASSPATH will need to contain: * Example of using the time series forecasting API. Post Views: 5,129 weka time series forecasting java eclipse weka time series forecasting java eclipse Program:
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