public SentimentAnnotator(string name, Properties props)
{
this.modelPath = props.GetProperty(name + ".model", DefaultModel);
if (modelPath == null)
{
throw new ArgumentException("No model specified for Sentiment annotator");
}
this.model = SentimentModel.LoadSerialized(modelPath);
}
public static async Task <SentimentPrediction> PredictSentimentAsync(SentimentModel predictData)
{
if (MLTraining.SentimentModel == null)
{
MLTraining.SentimentModel = await MLTraining.SentimentTrainAsync();
}
var prediction = MLTraining.SentimentModel.Predict(predictData);
return(prediction);
}
public IEnumerator TestCreateSentimentModel()
{
Log.Debug("NaturalLanguageUnderstandingServiceV1IntegrationTests", "Attempting to CreateSentimentModel...");
SentimentModel createSentimentModelResponse = null;
string modelId = "";
MemoryStream trainingData = new MemoryStream(ASCIIEncoding.Default.GetBytes("This is a mock file."));
service.CreateSentimentModel(
callback: (DetailedResponse <SentimentModel> response, IBMError error) =>
{
Log.Debug("NaturalLanguageUnderstandingServiceV1IntegrationTests", "CreateSentimentModel result: {0}", response.Response);
createSentimentModelResponse = response.Result;
Assert.IsNotNull(createSentimentModelResponse);
Assert.AreEqual(createSentimentModelResponse.Name, "testString");
Assert.AreEqual(createSentimentModelResponse.Language, "en");
Assert.AreEqual(createSentimentModelResponse.Description, "testString");
Assert.AreEqual(createSentimentModelResponse.ModelVersion, "testString");
Assert.AreEqual(createSentimentModelResponse.VersionDescription, "testString");
Assert.IsNull(error);
modelId = createSentimentModelResponse.ModelId;
},
language: "en",
trainingData: trainingData,
name: "testString",
description: "testString",
modelVersion: "testString",
versionDescription: "testString"
);
while (createSentimentModelResponse == null)
{
yield return(null);
}
DeleteModelResults deleteModelResults = null;
service.DeleteSentimentModel(
callback: (DetailedResponse <DeleteModelResults> response, IBMError error) =>
{
Log.Debug("NaturalLanguageUnderstandingServiceV1IntegrationTests", "DeleteSentimentModel result: {0}", response.Response);
deleteModelResults = response.Result;
Assert.IsNull(error);
},
modelId: modelId
);
while (deleteModelResults == null)
{
yield return(null);
}
}
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}");
}
}
private static List <SentimentModel> UseModelWithSingleItem(MLContext mlContext, ITransformer model, List <SentimentData> dataModelList)
{
var sentimentDataResult = new List <SentimentModel>();
PredictionEngine <SentimentData, SentimentPrediction> predictionFunction = mlContext.Model.CreatePredictionEngine <SentimentData, SentimentPrediction>(model);
foreach (var dataModel in dataModelList)
{
var resultPrediction = predictionFunction.Predict(dataModel);
var tempSentimentModel = new SentimentModel
{
Text = resultPrediction.SentimentText,
Location = resultPrediction.Location,
SentimentValue = resultPrediction.Probability
};
sentimentDataResult.Add(tempSentimentModel);
}
return(sentimentDataResult);
}
public IHttpActionResult GetSentimentVanPersoon(string id)
{
int intID = -1;
try
{
intID = int.Parse(id);
}
catch
{
return(NotFound());
}
List <Bericht> berichts = berichtMng.GetBerichten(b => b.Personen.FirstOrDefault(p => p.ID == intID) != null).ToList();
SentimentModel model = new SentimentModel()
{
Naam = berichtMng.GetPersoon(intID).Naam,
Objectiviteit = berichts.Average(b => b.Objectiviteit),
Polariteit = berichts.Average(b => b.Polariteit)
};
return(Ok(model));
}
public IndexModel(ILogger <IndexModel> logger, SentimentModel sentimentModel)
{
_logger = logger;
_sentimentModel = sentimentModel;
}