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sentiment3 taxonomy

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  1. Features Overview | Documentation

    GroupDocs.Classification main feature is an ability to classify raw text and documents with IAB-2, Documents, Sentiment or Sentiment3 taxonomies. Sentiment Classification (Analysis) supports 4 languages: English, Chinese, Spanish, and German. GroupDocs.Classification provides flexible set of settings to customize classification process: Name Description Default value bestClassesCount Select the number of results to return 1 Taxonomy Select Taxonomy (IAB-2, Documents, Sentiment or Sentiment3). Taxonomy.Iab2 precisionRecallBalance Select precision/recall balance for Documents Taxonomy. If the classifier is not sure of the result, it will return Other class.... Documents, Sentiment or Sentiment3 . Sentiment Classification...number of results to return 1 taxonomy Select (IAB-2, Documents,...

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  2. Taxonomies | Documentation

    Taxonomy Taxonomy (general)is the practice and science of classification of things or concepts, including the principles that underlie such classification. In our case, this is a list of text categories. We support two taxonomies for now: IAB-2 Taxonomy IAB-2 Taxonomy: https://www.iab.com/guidelines/Taxonomy/. Automotive, Books_and_Literature, Business_and_Finance, Careers, Education, Events_and_Attractions, Family_and_Relationships, Fine_Art, Food_&_Drink, Healthy_Living, Hobbies_&_Interests, Home_&_Garden, Medical_Health, Movies, Music_and_Audio, News_and_Politics, Personal_Finance, Pets, Pop_Culture, Real_Estate, Religion_&_Spirituality, Science, Shopping, Sports, Style_&_Fashion, Technology_&_Computing, Television, Travel, Video_Gaming Documents Taxonomy Documents Taxonomy:...Guide / Taxonomies Taxonomies Leave feedback Taxonomy is the practice...support two taxonomies for now: IAB-2 taxonomy IAB-2 taxonomy: . Automotive...

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  3. Sentiment classification usage | Documentation

    Create an instance of SentimentClassifier class. It is multilingual and supports English, Chinese, Spanish, and German. Creates SentimentClassifier instance var sentimentClassifier = new SentimentClassifier(); and call PositiveProbability method Classifies sentiment by text var positiveProbability = sentimentClassifier.PositiveProbability("This is a new must-have thing."); Console.WriteLine($"The probability of a positive sentiment is { positiveProbability }"); or call Classify method Classifies sentiment by text var response = sentimentClassifier.Classify("This is a new must-have thing."); Console.WriteLine($"The best class name:{response....sentiment by text with 3 classes taxonomy (Negative/Neutral/Positive)...must-have thing." , taxonomy : Taxonomy . Sentiment3 ); Console . WriteLine...

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