private static Task ClassifyAsync(
IModelDefinitionBuilder <SpamInput, MulticlassClassificationFoldsAverageMetricsResult> modelBuilder,
string text,
string expectedResult,
ILogger logger,
CancellationToken cancellationToken)
{
return(Task.Run(
() =>
{
var predictor = modelBuilder.MLContext.Model.CreatePredictionEngine <SpamInput, SpamPrediction>(modelBuilder.Model);
var input = new SpamInput {
Message = text
};
var prediction = predictor.Predict(input);
var result = prediction.IsSpam == "spam" ? "spam" : "not spam";
if (prediction.IsSpam == expectedResult)
{
logger.LogInformation("[ClassifyAsync][Predict] result: '{0}' is {1}", input.Message, result);
}
else
{
logger.LogWarning("[ClassifyAsync][Predict] result: '{0}' is {1}", input.Message, result);
}
},
cancellationToken));
}
private static Task ClassifyAsync(
IModelDefinitionBuilder <SentimentIssue, BinaryClassificationMetricsResult> modelBuilder,
string text,
bool expectedResult,
ILogger logger,
CancellationToken cancellationToken)
{
return(Task.Run(
() =>
{
var predictor = modelBuilder.MLContext.Model.CreatePredictionEngine <SentimentIssue, SentimentPrediction>(modelBuilder.Model);
var input = new SentimentIssue {
Text = text
};
var prediction = predictor.Predict(input);
var result = prediction.Prediction ? "Toxic" : "Non Toxic";
if (prediction.Prediction == expectedResult)
{
logger.LogInformation(
"[ClassifyAsync][Predict] result: '{0}' is {1} Probability of being toxic: {2}",
input.Text,
result,
prediction.Probability);
}
else
{
logger.LogWarning(
"[ClassifyAsync][Predict] result: '{0}' is {1} Probability of being toxic: {2}",
input.Text,
result,
prediction.Probability);
}
},
cancellationToken));
}