/** * Returns the error of the probability estimates for the current model on a * set of instances. * * @param data the set of instances * @return the error * @throws Exception if something goes wrong */ protected double getMeanAbsoluteError(Instances data) throws Exception { Evaluation eval = new Evaluation(data); eval.evaluateModel(this, data); return eval.meanAbsoluteError(); }
/** * Returns the error of the probability estimates for the current model on a * set of instances. * * @param data the set of instances * @return the error * @throws Exception if something goes wrong */ protected double getMeanAbsoluteError(Instances data) throws Exception { Evaluation eval = new Evaluation(data); eval.evaluateModel(this, data); return eval.meanAbsoluteError(); }
@Override public void execute() throws Exception { File storage = getContext().getStorageLocation(TestTask.OUTPUT_KEY, AccessMode.READONLY); Properties props = new Properties(); File evaluationFile = new File(storage.getAbsolutePath() + "/" + TestTask.EVALUATION_DATA_KEY); weka.classifiers.Evaluation eval = (weka.classifiers.Evaluation) SerializationHelper .read(evaluationFile.getAbsolutePath()); HashMap<String, Double> m = new HashMap<String, Double>(); m.put(CORRELATION, eval.correlationCoefficient()); m.put(MEAN_ABSOLUTE_ERROR, eval.meanAbsoluteError()); m.put(RELATIVE_ABSOLUTE_ERROR, eval.relativeAbsoluteError()); m.put(ROOT_MEAN_SQUARED_ERROR, eval.rootMeanSquaredError()); m.put(ROOT_RELATIVE_SQUARED_ERROR, eval.rootRelativeSquaredError()); for (String s : m.keySet()) { props.setProperty(s, m.get(s).toString()); } // Write out properties getContext().storeBinary(TestTask.RESULTS_KEY, new PropertiesAdapter(props)); } }
result[current++] = new Double(eval.avgCost()); result[current++] = new Double(eval.meanAbsoluteError()); result[current++] = new Double(eval.rootMeanSquaredError()); result[current++] = new Double(eval.relativeAbsoluteError());
result[current++] = new Double(eval.avgCost()); result[current++] = new Double(eval.meanAbsoluteError()); result[current++] = new Double(eval.rootMeanSquaredError()); result[current++] = new Double(eval.relativeAbsoluteError());
result[current++] = new Double(eval.numInstances()); result[current++] = new Double(eval.meanAbsoluteError()); result[current++] = new Double(eval.rootMeanSquaredError()); result[current++] = new Double(eval.relativeAbsoluteError());
result[current++] = new Double(eval.numInstances()); result[current++] = new Double(eval.meanAbsoluteError()); result[current++] = new Double(eval.rootMeanSquaredError()); result[current++] = new Double(eval.relativeAbsoluteError());
result[current++] = new Double(eval.kappa()); result[current++] = new Double(eval.meanAbsoluteError()); result[current++] = new Double(eval.rootMeanSquaredError()); result[current++] = new Double(eval.relativeAbsoluteError());
result[current++] = new Double(eval.kappa()); result[current++] = new Double(eval.meanAbsoluteError()); result[current++] = new Double(eval.rootMeanSquaredError()); result[current++] = new Double(eval.relativeAbsoluteError());
return -m_evaluation.rootMeanSquaredError(); case EVAL_MAE: return -m_evaluation.meanAbsoluteError(); case EVAL_AUC: double[] classPriors = m_evaluation.getClassPriors();
return -m_evaluation.rootMeanSquaredError(); case EVAL_MAE: return -m_evaluation.meanAbsoluteError(); case EVAL_AUC: double[] classPriors = m_evaluation.getClassPriors();
break; case EVAL_MAE: evalMetric = evaluation.meanAbsoluteError(); break; case EVAL_FMEASURE:
break; case EVAL_MAE: evalMetric = evaluation.meanAbsoluteError(); break; case EVAL_FMEASURE:
break; case EVAL_MAE: evalMetric = evaluation.meanAbsoluteError(); break; case EVAL_FMEASURE:
break; case EVAL_MAE: evalMetric = evaluation.meanAbsoluteError(); break; case EVAL_FMEASURE:
break; case EVAL_MAE: repError[i] = m_Evaluation.meanAbsoluteError(); break; case EVAL_FMEASURE:
break; case EVAL_MAE: repError[i] = m_Evaluation.meanAbsoluteError(); break; case EVAL_FMEASURE:
return m_Evaluation.rootRelativeSquaredError(); case DefaultEvaluationMetrics.EVALUATION_MAE: return m_Evaluation.meanAbsoluteError(); case DefaultEvaluationMetrics.EVALUATION_RAE: return m_Evaluation.relativeAbsoluteError();