/** * Retrieves all parameters without a name space. * * @return the settings map * * @deprecated use {@link #getObjectSettings()} instead */ public Map<String, String> getSettings() { return getSettings(null); }
private static void assertEquals(TrainingParameters expected, TrainingParameters actual) { if (expected == null) { Assert.assertNull(actual); } else { assertEquals(expected.getSettings(), actual); } } }
@Test public void testGetSettings() { TrainingParameters tp = build("k1=v1,n1.k2=v2,n2.k3=v3,n1.k4=v4"); assertEquals(buildMap("k1=v1"), tp.getSettings()); assertEquals(buildMap("k2=v2,k4=v4"), tp.getSettings("n1")); assertEquals(buildMap("k3=v3"), tp.getSettings("n2")); Assert.assertTrue(tp.getSettings("n3").isEmpty()); }
private static void assertEquals(Map<String, String> map, TrainingParameters actual) { Assert.assertNotNull(actual); assertEquals(map, actual.getSettings()); }
/** * Retrieves all parameters without a name space. * * @return the settings map * * @deprecated use {@link #getObjectSettings()} instead */ public Map<String, String> getSettings() { return getSettings(null); }
public static String getSentenceFeatures(TrainingParameters params) { String sentenceFlag = null; if (params.getSettings().get("SentenceFeatures") != null) { sentenceFlag = params.getSettings().get("SentenceFeatures"); } else { sentenceFlag = Flags.DEFAULT_FEATURE_FLAG; } return sentenceFlag; }
public static String getBigramClassFeatures(TrainingParameters params) { String bigramClassFlag = null; if (params.getSettings().get("BigramClassFeatures") != null) { bigramClassFlag = params.getSettings().get("BigramClassFeatures"); } else { bigramClassFlag = Flags.DEFAULT_FEATURE_FLAG; } return bigramClassFlag; }
public static String getMFSFeatures(TrainingParameters params) { String mfsFlag = null; if (params.getSettings().get("MFSFeatures") != null) { mfsFlag = params.getSettings().get("MFSFeatures"); } else { mfsFlag = Flags.DEFAULT_FEATURE_FLAG; } return mfsFlag; }
public static String getSuperSenseFeaturesRange(TrainingParameters params) { String mfsRangeFlag = null; if (params.getSettings().get("SuperSenseFeaturesRange") != null) { mfsRangeFlag = params.getSettings().get("SuperSenseFeaturesRange"); } else { mfsRangeFlag = Flags.DEFAULT_SUPERSENSE_RANGE; } return mfsRangeFlag; }
public static String getDictionaryFeatures(final TrainingParameters params) { String dictionaryFlag = null; if (params.getSettings().get("DictionaryFeatures") != null) { dictionaryFlag = params.getSettings().get("DictionaryFeatures"); } else { dictionaryFlag = Flags.DEFAULT_DICT_PATH; } return dictionaryFlag; }
public static String getClearEvaluationFeatures(TrainingParameters params) { String clearFeatures = null; if (params.getSettings().get("ClearEvaluationFeatures") == null) { clearFeatures = Flags.DEFAULT_FEATURE_FLAG; } else { clearFeatures = params.getSettings().get("ClearEvaluationFeatures"); } return clearFeatures; }
public static String getPreffixFeatures(TrainingParameters params) { String prefixFlag = null; if (params.getSettings().get("PrefixFeatures") != null) { prefixFlag = params.getSettings().get("PrefixFeatures"); } else { prefixFlag = Flags.DEFAULT_FEATURE_FLAG; } return prefixFlag; }
public static String getFivegramClassFeatures(TrainingParameters params) { String fivegramClassFlag = null; if (params.getSettings().get("FivegramClassFeatures") != null) { fivegramClassFlag = params.getSettings().get("FivegramClassFeatures"); } else { fivegramClassFlag = Flags.DEFAULT_FEATURE_FLAG; } return fivegramClassFlag; }
public static String getWord2VecClusterFeatures(TrainingParameters params) { String word2vecFlag = null; if (params.getSettings().get("Word2VecClusterFeatures") != null) { word2vecFlag = params.getSettings().get("Word2VecClusterFeatures"); } else { word2vecFlag = Flags.DEFAULT_FEATURE_FLAG; } return word2vecFlag; }
public static Integer getBeamsize(final TrainingParameters params) { Integer beamsize = null; if (params.getSettings().get("BeamSize") == null) { beamsize = Flags.DEFAULT_BEAM_SIZE; } else { beamsize = Integer.parseInt(params.getSettings().get("BeamSize")); } return beamsize; }
public static Integer getAutoDictFeatures(final TrainingParameters params) { String dictionaryFlag = null; if (params.getSettings().get("AutoDictFeatures") != null) { dictionaryFlag = params.getSettings().get("AutoDictFeatures"); } else { dictionaryFlag = Integer.toString(Flags.DEFAULT_DICT_CUTOFF); } return Integer.parseInt(dictionaryFlag); }
public static String getDataSet(String dataset, TrainingParameters params) { String trainSet = null; if (params.getSettings().get(dataset) == null) { datasetException(); } else { trainSet = params.getSettings().get(dataset); } return trainSet; }
@Test public void testDefault() { TrainingParameters tr = TrainingParameters.defaultParams(); Assert.assertEquals(4, tr.getSettings().size()); Assert.assertEquals("MAXENT", tr.algorithm()); Assert.assertEquals(EventTrainer.EVENT_VALUE, tr.getStringParameter(TrainingParameters.TRAINER_TYPE_PARAM, "v11")); // use different defaults Assert.assertEquals(100, tr.getIntParameter(TrainingParameters.ITERATIONS_PARAM, 200)); // use different defaults Assert.assertEquals(5, tr.getIntParameter(TrainingParameters.CUTOFF_PARAM, 200)); // use different defaults }
@Test public void testGetParameters() { TrainingParameters tp = build("k1=v1,n1.k2=v2,n2.k3=v3,n1.k4=v4"); assertEquals(build("k1=v1"), tp.getParameters(null)); assertEquals(build("k2=v2,k4=v4"), tp.getParameters("n1")); assertEquals(build("k3=v3"), tp.getParameters("n2")); Assert.assertTrue(tp.getParameters("n3").getSettings().isEmpty()); }
private void getEvalListeners(TrainingParameters params) { if (params.getSettings().get("EvaluationType").equalsIgnoreCase("error")) { listeners.add(new NameEvaluationErrorListener()); } if (params.getSettings().get("EvaluationType").equalsIgnoreCase("detailed")) { detailedFListener = new TokenNameFinderDetailedFMeasureListener(); listeners.add(detailedFListener); } }