List of usage examples for org.apache.mahout.classifier.df.data DataLoader loadData
public static Data loadData(Dataset dataset, FileSystem fs, Path[] pathes) throws IOException
From source file:bigimp.BuildForest.java
License:Apache License
protected static Data loadData(Configuration conf, Path dataPath, Dataset dataset) throws IOException { log.info("Loading the data..."); FileSystem fs = dataPath.getFileSystem(conf); Data data = DataLoader.loadData(dataset, fs, dataPath); log.info("Data Loaded"); return data;/*from w w w.j a va2 s .com*/ }
From source file:javaapplication3.runRandomForest.java
public static void main(String[] args) throws InterruptedException, IOException, ClassNotFoundException { String outputFile = "data/lule24"; String inputFile = "data/DataFraud1MTest.csv"; String modelFile = "data/forest.seq"; String infoFile = "data/DataFraud1M.info"; Path dataPath = new Path(inputFile); // test data path Path datasetPath = new Path(infoFile); Path modelPath = new Path(modelFile); // path where the forest is stored Path outputPath = new Path(outputFile); // path to predictions file, if null do not output the predictions Configuration conf = new Configuration(); FileSystem fs = FileSystem.get(conf); /*/*from w w w .j a v a 2 s. c om*/ p = Runtime.getRuntime().exec("bash /home/ivan/hadoop-1.2.1/bin/start-all.sh"); p.waitFor();*/ if (outputPath == null) { throw new IllegalArgumentException( "You must specify the ouputPath when using the mapreduce implementation"); } Classifier classifier = new Classifier(modelPath, dataPath, datasetPath, outputPath, conf); classifier.run(); double[][] results = classifier.getResults(); if (results != null) { Dataset dataset = Dataset.load(conf, datasetPath); Data data = DataLoader.loadData(dataset, fs, dataPath); Instance inst; for (int i = 0; i < data.size(); i++) { inst = data.get(i); //System.out.println("Prediction:"+inst.get(7)+" Real value:"+results[i][1]); System.out.println(inst.get(0) + " " + inst.get(1) + " " + inst.get(2) + " " + inst.get(3) + " " + inst.get(4) + " " + inst.get(5) + " " + inst.get(6) + " " + inst.get(7) + " "); } ResultAnalyzer analyzer = new ResultAnalyzer(Arrays.asList(dataset.labels()), "unknown"); for (double[] res : results) { analyzer.addInstance(dataset.getLabelString(res[0]), new ClassifierResult(dataset.getLabelString(res[1]), 1.0)); System.out.println("Prvi shit:" + res[0] + " Drugi Shit" + res[1]); } System.out.println(analyzer.toString()); } }