@Override public ReportBase getOutcomeIdReportClass() { return new DeepLearningId2OutcomeReport(); }
protected void init() { isMultiLabel = getDiscriminator(getContext(), DIM_LEARNING_MODE).equals(LM_MULTI_LABEL); isRegression = getDiscriminator(getContext(), DIM_LEARNING_MODE).equals(LM_REGRESSION); if (isMultiLabel) { THRESHOLD = getDiscriminator(getContext(), DIM_BIPARTITION_THRESHOLD); } isIntegerMode = Boolean.valueOf(getDiscriminator(getContext(), DIM_VECTORIZE_TO_INTEGER)); }
init(); baselinePreparation(); File file = getContext().getFile(FILENAME_PREDICTION_OUT, AccessMode.READONLY); List<String> predictions = getPredictions(file); predictions = update(predictions); Map<String, String> map = loadMap(isIntegerMode); Map<String, String> inverseMap = inverseMap(map); List<String> nameOfTargets = getNameOfTargets(); StringBuilder sb = new StringBuilder(); String id = determineId(nameOfTargets, i, shift); sb = multilabelReport(id, split, isIntegerMode, sb, map); continue; File id2o = getTargetFile(); FileUtils.writeStringToFile(id2o, data, "utf-8");
protected File getTargetFile() { return getContext().getFile(Constants.ID_OUTCOME_KEY, AccessMode.READWRITE); }
@Override public void execute() throws Exception { init(); if (isRegression) { return; } super.execute(); }
init(); baselinePreparation(); File file = getContext().getFile(FILENAME_PREDICTION_OUT, AccessMode.READONLY); List<String> predictions = getPredictions(file); predictions = update(predictions); Map<String, String> map = loadMap(isIntegerMode); Map<String, String> inverseMap = inverseMap(map); List<String> nameOfTargets = getNameOfTargets(); StringBuilder sb = new StringBuilder(); String id = determineId(nameOfTargets, i, shift); sb = multilabelReport(id, split, isIntegerMode, sb, map); continue; File id2o = getTargetFile(); FileUtils.writeStringToFile(id2o, data, "utf-8");
protected File getTargetFile() { return getContext().getFile(Constants.ID_OUTCOME_KEY, AccessMode.READWRITE); }
@Override public void execute() throws Exception { init(); if (isRegression) { return; } super.execute(); }
@Override public ReportBase getOutcomeIdReportClass() { return new DeepLearningId2OutcomeReport(); }
protected void init() { isMultiLabel = getDiscriminator(getContext(), DIM_LEARNING_MODE).equals(LM_MULTI_LABEL); isRegression = getDiscriminator(getContext(), DIM_LEARNING_MODE).equals(LM_REGRESSION); if (isMultiLabel) { THRESHOLD = getDiscriminator(getContext(), DIM_BIPARTITION_THRESHOLD); } isIntegerMode = Boolean.valueOf(getDiscriminator(getContext(), DIM_VECTORIZE_TO_INTEGER)); }
private List<String> getNameOfTargets() throws IOException { File targetIdMappingFolder = getContext() .getFolder(TcDeepLearningAdapter.TARGET_ID_MAPPING_TEST, AccessMode.READONLY); File targetIdMappingFile = new File(targetIdMappingFolder, DeepLearningConstants.FILENAME_TARGET_ID_TO_INDEX); List<String> t = new ArrayList<>(); List<String> readLines = FileUtils.readLines(targetIdMappingFile, "utf-8"); for (String s : readLines) { if (s.startsWith("#")) { continue; } if (s.isEmpty()) { t.add(""); continue; } String[] split = s.split("\t"); if (split[0].contains("_")) { t.add(s.replaceAll("\t", "_")); } else { t.add(split[1]); } } return t; }
@Override public void execute() throws Exception { init(); if (isRegression) { return; } super.execute(); }
@Override public ReportBase getOutcomeIdReportClass() { return new DeepLearningId2OutcomeReport(); }
private List<String> getNameOfTargets() throws IOException { File targetIdMappingFolder = getContext() .getFolder(TcDeepLearningAdapter.TARGET_ID_MAPPING_TEST, AccessMode.READONLY); File targetIdMappingFile = new File(targetIdMappingFolder, DeepLearningConstants.FILENAME_TARGET_ID_TO_INDEX); List<String> t = new ArrayList<>(); List<String> readLines = FileUtils.readLines(targetIdMappingFile, "utf-8"); for (String s : readLines) { if (s.startsWith("#")) { continue; } if (s.isEmpty()) { t.add(""); continue; } String[] split = s.split("\t"); if (split[0].contains("_")) { t.add(s.replaceAll("\t", "_")); } else { t.add(split[1]); } } return t; }
@Override public void execute() throws Exception { init(); if (isRegression) { return; } super.execute(); }
File prepFolder = getContext().getFolder(TcDeepLearningAdapter.PREPARATION_FOLDER, AccessMode.READONLY); File mapping = new File(prepFolder, DeepLearningConstants.FILENAME_OUTCOME_MAPPING); File prepFolder = getContext().getFolder(TcDeepLearningAdapter.PREPARATION_FOLDER, AccessMode.READONLY); File file = new File(prepFolder, DeepLearningConstants.FILENAME_OUTCOMES);
File prepFolder = getContext().getFolder(TcDeepLearningAdapter.PREPARATION_FOLDER, AccessMode.READONLY); File mapping = new File(prepFolder, DeepLearningConstants.FILENAME_OUTCOME_MAPPING); File prepFolder = getContext().getFolder(TcDeepLearningAdapter.PREPARATION_FOLDER, AccessMode.READONLY); File file = new File(prepFolder, DeepLearningConstants.FILENAME_OUTCOMES);