public void Reset() { PersonOccurenceDatabase = new WordOccurenceDatabase(); OrganizationOccurenceDatabase = new WordOccurenceDatabase(); LocationsOccurenceDatabase = new WordOccurenceDatabase(); SportSpecificWordsOccurenceDatabase = new WordOccurenceDatabase(); int hiddenLayerCount = (10 * _categoriesCount) / 3; _classifier = new ActivationNetwork(new SigmoidFunction(), 4 * _categoriesCount, hiddenLayerCount, _categoriesCount); _teacher = new BackPropagationLearning(_classifier); }
public Marker(NLPProcessor processor, string modelPath) { _processor = processor; _modelPath = modelPath; Annotation sportSpecificWords = _processor.Annotate(File.ReadAllText(modelPath + "specificwords.txt")); _sportSpecificWords = NLPCoreHelper.GetLemmas(sportSpecificWords); File.Delete(modelPath + "specificwords.txt"); StringBuilder builder = new StringBuilder(); foreach (string word in _sportSpecificWords) { builder.AppendLine(word); } File.WriteAllText(modelPath + "specificwords.txt", builder.ToString()); PersonOccurenceDatabase = new WordOccurenceDatabase(); OrganizationOccurenceDatabase = new WordOccurenceDatabase(); LocationsOccurenceDatabase = new WordOccurenceDatabase(); SportSpecificWordsOccurenceDatabase = new WordOccurenceDatabase(); _categoriesCount = Enum.GetValues(typeof(SportCategory)).Length; int hiddenLayerCount = (10 * _categoriesCount) / 3; _classifier = new ActivationNetwork(new SigmoidFunction(), 4 * _categoriesCount, hiddenLayerCount, _categoriesCount); _teacher = new BackPropagationLearning(_classifier); Array values = Enum.GetValues(typeof(SportCategory)); _categoryIndex = new Dictionary <SportCategory, int>(); _indexCategory = new Dictionary <int, SportCategory>(); for (int index = 0; index < values.Length; index++) { SportCategory category = (SportCategory)values.GetValue(index); _categoryIndex.Add(category, index); _indexCategory.Add(index, category); } }