user.getUsername(), r.getName()); continue; log.debug("[{}][{}]: Disabled - skipping", user.getUsername(), r.getName()); continue; .collect(Collectors.toList()); log.info("[{}][{}]: Training model on [{}] out of [{}] documents ...", user.getUsername(), recommender.getName(), cassesForTraining.size(), casses.get().size()); recommender.getName(), (System.currentTimeMillis() - startTime)); recommender.getName(), (System.currentTimeMillis() - startTime), e);
@Override protected void onModelChanged() { super.onModelChanged(); // When field become invalid, Wicket stops re-rendering them. Thus we tell all of them that // their model has changes such that they clear their validation status. visitChildren(new ModelChangedVisitor(recommenderModel)); // Since toolChoice uses a lambda model, it needs to be notified explicitly. toolChoice.modelChanged(); // For new recommenders, default to auto-generation of name, for existing recommenders, // do not auto-generate name unless asked to Recommender recommender = recommenderModel.getObject(); if ( recommender.getId() == null || Objects.equals(recommender.getName(), generateName(recommender)) ) { autoGenerateNameCheckBox.setModelObject(true); autoUpdateName(null, nameField, recommenderModel.getObject()); } else { autoGenerateNameCheckBox.setModelObject(false); } }
.orElse(NO_SCORE); String featurename = aRecommender.getFeature().getName(); String name = aRecommender.getName(); "[{}]({}) for user [{}] on document " + "[{}]({}) in project [{}]({}) generated {} predictions.", aRecommender.getName(), aRecommender.getId(), aUser.getUsername(), aDocument.getName(), aDocument.getId(), aRecommender.getProject().getName(), aRecommender.getProject().getId(), predictionCount);
recommenderScoreMap.put(recommenderIfActive.get(0).getName(), detail.score);
user.getUsername(), r.getName()); continue nextRecommender; log.debug("[{}][{}]: Disabled - skipping", user.getUsername(), r.getName()); continue nextRecommender; log.info("Context for recommender [{}]({}) for user [{}] on document " + "[{}]({}) in project [{}]({}) is not ready yet - skipping recommender", recommender.getName(), recommender.getId(), user.getUsername(), document.getName(), document.getId(), project.getName(), project.getId()); log.error("Error applying recommender [{}]({}) for user [{}] to document " + "[{}]({}) in project [{}]({}) - skipping recommender", recommender.getName(), recommender.getId(), user.getUsername(), document.getName(), document.getId(), project.getName(), project.getId(), e);
@Override public void exportData(ProjectExportRequest aRequest, ExportedProject aExProject, File aFile) { Project project = aRequest.getProject(); List<ExportedRecommender> exportedRecommenders = new ArrayList<>(); for (Recommender recommender : recommendationService.listRecommenders(project)) { ExportedRecommender exportedRecommender = new ExportedRecommender(); exportedRecommender.setAlwaysSelected(recommender.isAlwaysSelected()); exportedRecommender.setFeature(recommender.getFeature().getName()); exportedRecommender.setEnabled(recommender.isEnabled()); exportedRecommender.setLayerName(recommender.getLayer().getName()); exportedRecommender.setName(recommender.getName()); exportedRecommender.setThreshold(recommender.getThreshold()); exportedRecommender.setTool(recommender.getTool()); exportedRecommender.setSkipEvaluation(recommender.isSkipEvaluation()); exportedRecommender.setMaxRecommendations(recommender.getMaxRecommendations()); exportedRecommender.setStatesIgnoredForTraining( recommender.getStatesIgnoredForTraining()); exportedRecommender.setTraits(recommender.getTraits()); exportedRecommenders.add(exportedRecommender); } aExProject.setProperty(KEY, exportedRecommenders); int n = exportedRecommenders.size(); LOG.info("Exported [{}] recommenders for project [{}]", n, project.getName()); }