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/* * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see <http://www.gnu.org/licenses/>. */ /* * WekaEvaluationValuePicker.java * Copyright (C) 2009-2015 University of Waikato, Hamilton, New Zealand */ package adams.flow.transformer; import adams.core.QuickInfoHelper; import adams.data.weka.WekaLabelIndex; import adams.flow.container.WekaEvaluationContainer; import adams.flow.core.EvaluationHelper; import adams.flow.core.EvaluationStatistic; import adams.flow.core.Token; import weka.classifiers.Evaluation; /** <!-- globalinfo-start --> * Picks a specific value from an evaluation object. * <br><br> <!-- globalinfo-end --> * <!-- flow-summary-start --> * Input/output:<br> * - accepts:<br> * weka.classifiers.Evaluation<br> * - generates:<br> * java.lang.Double<br> * <br><br> <!-- flow-summary-end --> * <!-- options-start --> * Valid options are: <br><br> * * <pre>-D (property: debug) * If set to true, scheme may output additional info to the console. * </pre> * * <pre>-name <java.lang.String> (property: name) * The name of the actor. * default: EvaluationValuePicker * </pre> * * <pre>-annotation <adams.core.base.BaseText> (property: annotations) * The annotations to attach to this actor. * default: * </pre> * * <pre>-skip (property: skip) * If set to true, transformation is skipped and the input token is just forwarded * as it is. * </pre> * * <pre>-statistic <ELAPSED_TIME_TRAINING|ELAPSED_TIME_TESTING|USERCPU_TIME_TRAINING|USERCPU_TIME_TESTING|SERIALIZED_MODEL_SIZE|SERIALIZED_TRAIN_SET_SIZE|SERIALIZED_TEST_SET_SIZE|NUMBER_OF_TRAINING_INSTANCES|NUMBER_OF_TESTING_INSTANCES|NUMBER_CORRECT|NUMBER_INCORRECT|NUMBER_UNCLASSIFIED|PERCENT_CORRECT|PERCENT_INCORRECT|PERCENT_UNCLASSIFIED|KAPPA_STATISTIC|MEAN_ABSOLUTE_ERROR|ROOT_MEAN_SQUARED_ERROR|RELATIVE_ABSOLUTE_ERROR|ROOT_RELATIVE_SQUARED_ERROR|CORRELATION_COEFFICIENT|SF_PRIOR_ENTROPY|SF_SCHEME_ENTROPY|SF_ENTROPY_GAIN|SF_MEAN_PRIOR_ENTROPY|SF_MEAN_SCHEME_ENTROPY|SF_MEAN_ENTROPY_GAIN|KB_INFORMATION|KB_MEAN_INFORMATION|KB_RELATIVE_INFORMATION|TRUE_POSITIVE_RATE|NUM_TRUE_POSITIVES|FALSE_POSITIVE_RATE|NUM_FALSE_POSITIVES|TRUE_NEGATIVE_RATE|NUM_TRUE_NEGATIVES|FALSE_NEGATIVE_RATE|NUM_FALSE_NEGATIVES|IR_PRECISION|IR_RECALL|F_MEASURE|AREA_UNDER_ROC> (property: statisticValue) * The evaluation value to extract. * default: PERCENT_CORRECT * </pre> * * <pre>-index <int> (property: classIndex) * The class label index (eg used for AUC). * default: 1 * </pre> * <!-- options-end --> * * @author fracpete (fracpete at waikato dot ac dot nz) * @version $Revision$ */ public class WekaEvaluationValuePicker extends AbstractTransformer { /** for serialization. */ private static final long serialVersionUID = -3113058781746945626L; /** the comparison field. */ protected EvaluationStatistic m_StatisticValue; /** the index of the class label. */ protected WekaLabelIndex m_ClassIndex; /** * Returns a string describing the object. * * @return a description suitable for displaying in the gui */ @Override public String globalInfo() { return "Picks a specific value from an evaluation object."; } /** * Adds options to the internal list of options. */ @Override public void defineOptions() { super.defineOptions(); m_OptionManager.add("statistic", "statisticValue", EvaluationStatistic.PERCENT_CORRECT); m_OptionManager.add("index", "classIndex", new WekaLabelIndex(WekaLabelIndex.FIRST)); } /** * Sets the value to extract. * * @param value the value */ public void setStatisticValue(EvaluationStatistic value) { m_StatisticValue = value; reset(); } /** * Returns the value to extract. * * @return the value */ public EvaluationStatistic getStatisticValue() { return m_StatisticValue; } /** * Returns the tip text for this property. * * @return tip text for this property suitable for * displaying in the GUI or for listing the options. */ public String statisticValueTipText() { return "The evaluation value to extract."; } /** * Sets the class label index (1-based). * * @param value the label index */ public void setClassIndex(WekaLabelIndex value) { m_ClassIndex = value; reset(); } /** * Returns the current class label index (1-based). * * @return the label index */ public WekaLabelIndex getClassIndex() { return m_ClassIndex; } /** * Returns the tip text for this property. * * @return tip text for this property suitable for * displaying in the GUI or for listing the options. */ public String classIndexTipText() { return "The class label index (eg used for AUC)."; } /** * Returns a quick info about the actor, which will be displayed in the GUI. * * @return null if no info available, otherwise short string */ @Override public String getQuickInfo() { String result; result = QuickInfoHelper.toString(this, "classIndex", m_ClassIndex); result += QuickInfoHelper.toString(this, "statisticValue", m_StatisticValue, ": "); return result; } /** * Returns the class that the consumer accepts. * * @return <!-- flow-accepts-start -->weka.classifiers.Evaluation.class<!-- flow-accepts-end --> */ public Class[] accepts() { return new Class[] { Evaluation.class, WekaEvaluationContainer.class }; } /** * Executes the flow item. * * @return null if everything is fine, otherwise error message */ @Override protected String doExecute() { String result; double value; Evaluation eval; result = null; value = Double.NaN; if (m_InputToken.getPayload() instanceof WekaEvaluationContainer) eval = (Evaluation) ((WekaEvaluationContainer) m_InputToken.getPayload()) .getValue(WekaEvaluationContainer.VALUE_EVALUATION); else eval = (Evaluation) m_InputToken.getPayload(); try { m_ClassIndex.setData(eval.getHeader().classAttribute()); value = EvaluationHelper.getValue(eval, m_StatisticValue, m_ClassIndex.getIntIndex()); m_OutputToken = new Token(value); } catch (Exception e) { result = handleException("Error retrieving value for '" + m_StatisticValue + "':\n", e); } return result; } /** * Returns the class of objects that it generates. * * @return <!-- flow-generates-start -->java.lang.Double.class<!-- flow-generates-end --> */ public Class[] generates() { return new Class[] { Double.class }; } }