Exemplo n.º 1
0
        private static void SentimentTest()
        {
            var builder = new SentimentModel();

            var dataView = builder.LoadFromText("comment.tsv", allowQuoting: true);

            builder.Train(dataView);

            //var inputs = new List<SentimentData>();

            while (true)
            {
                var word = Console.ReadLine();
                if (string.Equals(word, "exit", StringComparison.CurrentCultureIgnoreCase))
                {
                    break;
                }

                //inputs.Add(new SentimentData
                //{
                //    SentimentText = word
                //});
                //if (inputs.Count < 3) continue;

                //var results = builder.Predict(inputs);
                //foreach (var result in results)
                //{
                //    Console.WriteLine($"Text\t\t:{result.SentimentText}");

                //    Console.WriteLine($"Prediction\t:{result.Prediction}");
                //    Console.WriteLine($"Probability\t:{result.Probability}");
                //    Console.WriteLine($"Score\t\t:{result.Score}");
                //}
                //inputs.Clear();

                var result = builder.Predict(new SentimentData
                {
                    SentimentText = word
                });

                Console.WriteLine($"Text\t\t:{result.SentimentText}");

                Console.WriteLine($"Prediction\t:{result.Prediction}");
                Console.WriteLine($"Probability\t:{result.Probability}");
                Console.WriteLine($"Score\t\t:{result.Score}");
            }
        }
Exemplo n.º 2
0
        public async Task OnPost()
        {
            ModelInput input = new ModelInput
            {
                Comment = _comment
            };

            try
            {
                ModelOutput    = _sentimentModel.Predict(input);
                ShowPrediction = true;
            }
            catch (HttpRequestException)
            {
                ModelOutput = new ModelOutput {
                    Prediction = ""
                };
            }
        }