List of usage examples for weka.classifiers CostMatrix CostMatrix
public CostMatrix(Reader reader) throws Exception
From source file:bme.mace.logicdomain.Evaluation.java
License:Open Source License
/** * Attempts to load a cost matrix.//from w ww . j a v a 2 s . c o m * * @param costFileName the filename of the cost matrix * @param numClasses the number of classes that should be in the cost matrix * (only used if the cost file is in old format). * @return a <code>CostMatrix</code> value, or null if costFileName is empty * @throws Exception if an error occurs. */ protected static CostMatrix handleCostOption(String costFileName, int numClasses) throws Exception { if ((costFileName != null) && (costFileName.length() != 0)) { System.out.println("NOTE: The behaviour of the -m option has changed between WEKA 3.0" + " and WEKA 3.1. -m now carries out cost-sensitive *evaluation*" + " only. For cost-sensitive *prediction*, use one of the" + " cost-sensitive metaschemes such as" + " weka.classifiers.meta.CostSensitiveClassifier or" + " weka.classifiers.meta.MetaCost"); Reader costReader = null; try { costReader = new BufferedReader(new FileReader(costFileName)); } catch (Exception e) { throw new Exception("Can't open file " + e.getMessage() + '.'); } try { // First try as a proper cost matrix format return new CostMatrix(costReader); } catch (Exception ex) { try { // Now try as the poxy old format :-) // System.err.println("Attempting to read old format cost file"); try { costReader.close(); // Close the old one costReader = new BufferedReader(new FileReader(costFileName)); } catch (Exception e) { throw new Exception("Can't open file " + e.getMessage() + '.'); } CostMatrix costMatrix = new CostMatrix(numClasses); // System.err.println("Created default cost matrix"); costMatrix.readOldFormat(costReader); return costMatrix; // System.err.println("Read old format"); } catch (Exception e2) { // re-throw the original exception // System.err.println("Re-throwing original exception"); throw ex; } } } else { return null; } }
From source file:cotraining.copy.Evaluation_D.java
License:Open Source License
/** * Attempts to load a cost matrix.//from ww w . j ava 2s . c om * * @param costFileName the filename of the cost matrix * @param numClasses the number of classes that should be in the cost matrix * (only used if the cost file is in old format). * @return a <code>CostMatrix</code> value, or null if costFileName is empty * @throws Exception if an error occurs. */ protected static CostMatrix handleCostOption(String costFileName, int numClasses) throws Exception { if ((costFileName != null) && (costFileName.length() != 0)) { System.out.println("NOTE: The behaviour of the -m option has changed between WEKA 3.0" + " and WEKA 3.1. -m now carries out cost-sensitive *evaluation*" + " only. For cost-sensitive *prediction*, use one of the" + " cost-sensitive metaschemes such as" + " weka.classifiers.meta.CostSensitiveClassifier or" + " weka.classifiers.meta.MetaCost"); Reader costReader = null; try { costReader = new BufferedReader(new FileReader(costFileName)); } catch (Exception e) { throw new Exception("Can't open file " + e.getMessage() + '.'); } try { // First try as a proper cost matrix format return new CostMatrix(costReader); } catch (Exception ex) { try { // Now try as the poxy old format :-) //System.err.println("Attempting to read old format cost file"); try { costReader.close(); // Close the old one costReader = new BufferedReader(new FileReader(costFileName)); } catch (Exception e) { throw new Exception("Can't open file " + e.getMessage() + '.'); } CostMatrix costMatrix = new CostMatrix(numClasses); //System.err.println("Created default cost matrix"); costMatrix.readOldFormat(costReader); return costMatrix; //System.err.println("Read old format"); } catch (Exception e2) { // re-throw the original exception //System.err.println("Re-throwing original exception"); throw ex; } } } else { return null; } }
From source file:etc.aloe.cscw2013.TrainingImpl.java
License:Open Source License
@Override public WekaModel train(ExampleSet examples) { System.out.println("SMO Options: " + SMO_OPTIONS); SMO smo = new SMO(); try {/*from w w w.j a v a2s . c om*/ smo.setOptions(Utils.splitOptions(SMO_OPTIONS)); } catch (Exception ex) { System.err.println("Unable to configure SMO."); System.err.println("\t" + ex.getMessage()); return null; } //Build logistic models if desired smo.setBuildLogisticModels(isBuildLogisticModel()); Classifier classifier = smo; if (useCostTraining) { CostSensitiveClassifier cost = new CostSensitiveClassifier(); cost.setClassifier(smo); CostMatrix matrix = new CostMatrix(2); matrix.setElement(0, 0, 0); matrix.setElement(0, 1, falsePositiveCost); matrix.setElement(1, 0, falseNegativeCost); matrix.setElement(1, 1, 0); cost.setCostMatrix(matrix); classifier = cost; System.out.print("Wrapping SMO in CostSensitiveClassifier " + matrix.toMatlab()); if (useReweighting) { cost.setMinimizeExpectedCost(false); System.out.println(" using re-weighting."); } else { cost.setMinimizeExpectedCost(true); System.out.println(" using min-cost criterion."); } } try { System.out.print("Training SMO on " + examples.size() + " examples... "); classifier.buildClassifier(examples.getInstances()); System.out.println("done."); WekaModel model = new WekaModel(classifier); return model; } catch (Exception ex) { System.err.println("Unable to train SMO."); System.err.println("\t" + ex.getMessage()); return null; } }
From source file:jjj.asap.sas.models1.job.BuildBasicMetaCostModels.java
License:Open Source License
@Override protected void run() throws Exception { // validate args if (!Bucket.isBucket("datasets", inputBucket)) { throw new FileNotFoundException(inputBucket); }//from w w w .j ava 2 s. c o m if (!Bucket.isBucket("models", outputBucket)) { throw new FileNotFoundException(outputBucket); } // create prototype classifiers Map<String, Classifier> prototypes = new HashMap<String, Classifier>(); // Bagged REPTrees Bagging baggedTrees = new Bagging(); baggedTrees.setNumExecutionSlots(1); baggedTrees.setNumIterations(100); baggedTrees.setClassifier(new REPTree()); baggedTrees.setCalcOutOfBag(false); prototypes.put("Bagged-REPTrees", baggedTrees); // Bagged SMO Bagging baggedSVM = new Bagging(); baggedSVM.setNumExecutionSlots(1); baggedSVM.setNumIterations(100); baggedSVM.setClassifier(new SMO()); baggedSVM.setCalcOutOfBag(false); prototypes.put("Bagged-SMO", baggedSVM); // Meta Cost model for Naive Bayes Bagging bagging = new Bagging(); bagging.setNumExecutionSlots(1); bagging.setNumIterations(100); bagging.setClassifier(new NaiveBayes()); CostSensitiveClassifier meta = new CostSensitiveClassifier(); meta.setClassifier(bagging); meta.setMinimizeExpectedCost(true); prototypes.put("CostSensitive-MinimizeExpectedCost-NaiveBayes", bagging); // init multi-threading Job.startService(); final Queue<Future<Object>> queue = new LinkedList<Future<Object>>(); // get the input from the bucket List<String> names = Bucket.getBucketItems("datasets", this.inputBucket); for (String dsn : names) { // for each prototype classifier for (Map.Entry<String, Classifier> prototype : prototypes.entrySet()) { // // speical logic for meta cost // Classifier alg = AbstractClassifier.makeCopy(prototype.getValue()); if (alg instanceof CostSensitiveClassifier) { int essaySet = Contest.getEssaySet(dsn); String matrix = Contest.getRubrics(essaySet).size() == 3 ? "cost3.txt" : "cost4.txt"; ((CostSensitiveClassifier) alg) .setCostMatrix(new CostMatrix(new FileReader("/asap/sas/trunk/" + matrix))); } // use InfoGain to discard useless attributes AttributeSelectedClassifier classifier = new AttributeSelectedClassifier(); classifier.setEvaluator(new InfoGainAttributeEval()); Ranker ranker = new Ranker(); ranker.setThreshold(0.0001); classifier.setSearch(ranker); classifier.setClassifier(alg); queue.add(Job.submit( new ModelBuilder(dsn, "InfoGain-" + prototype.getKey(), classifier, this.outputBucket))); } } // wait on complete Progress progress = new Progress(queue.size(), this.getClass().getSimpleName()); while (!queue.isEmpty()) { try { queue.remove().get(); } catch (Exception e) { Job.log("ERROR", e.toString()); } progress.tick(); } progress.done(); Job.stopService(); }
From source file:milk.classifiers.MIEvaluation.java
License:Open Source License
/** * Attempts to load a cost matrix.//from w w w . j a v a2s. c o m * * @param costFileName the filename of the cost matrix * @param numClasses the number of classes that should be in the cost matrix * (only used if the cost file is in old format). * @return a <code>CostMatrix</code> value, or null if costFileName is empty * @exception Exception if an error occurs. */ private static CostMatrix handleCostOption(String costFileName, int numClasses) throws Exception { if ((costFileName != null) && (costFileName.length() != 0)) { System.out.println("NOTE: The behaviour of the -m option has changed between WEKA 3.0" + " and WEKA 3.1. -m now carries out cost-sensitive *evaluation*" + " only. For cost-sensitive *prediction*, use one of the" + " cost-sensitive metaschemes such as" + " weka.classifiers.CostSensitiveClassifier or" + " weka.classifiers.MetaCost"); Reader costReader = null; try { costReader = new BufferedReader(new FileReader(costFileName)); } catch (Exception e) { throw new Exception("Can't open file " + e.getMessage() + '.'); } try { // First try as a proper cost matrix format return new CostMatrix(costReader); } catch (Exception ex) { try { // Now try as the poxy old format :-) //System.err.println("Attempting to read old format cost file"); try { costReader.close(); // Close the old one costReader = new BufferedReader(new FileReader(costFileName)); } catch (Exception e) { throw new Exception("Can't open file " + e.getMessage() + '.'); } CostMatrix costMatrix = new CostMatrix(numClasses); //System.err.println("Created default cost matrix"); costMatrix.readOldFormat(costReader); return costMatrix; //System.err.println("Read old format"); } catch (Exception e2) { // re-throw the original exception //System.err.println("Re-throwing original exception"); throw ex; } } } else { return null; } }
From source file:org.openml.webapplication.algorithm.InstancesHelper.java
License:Open Source License
public static CostMatrix doubleToCostMatrix(double[][] cm) { CostMatrix costmatrix = new CostMatrix(cm.length); for (int i = 0; i < cm.length; ++i) { for (int j = 0; j < cm[i].length; ++j) { costmatrix.setElement(i, j, cm[i][j]); }/*from w ww . j a v a 2 s . co m*/ } return costmatrix; }