public string Train(List <TrainData> data)
{
try {
mlContext = new MLContext();
splitDataView = Metrics.Look(() => mlContext.LoadData(data));
model = Metrics.Look(() => mlContext.BuildAndTrainModel(splitDataView));
return("Ok");
} catch (Exception e) {
return(e.StackTrace);
}
}
static void Main(string[] args)
{
var mlContext = new MLContext();
string dataFilePath = Path.Combine(Environment.CurrentDirectory, @"Data\yelp_labelled.txt");
var splitDataView = mlContext.LoadData(dataFilePath);
ITransformer model = mlContext.BuildAndTrainModel(splitDataView.TrainSet);
var metrics = mlContext.Evaluate(model, splitDataView.TestSet);
Console.WriteLine("\r\n--------------- Model quality metrics evaluation ---------------");
Console.WriteLine($"Accuracy: {metrics.Accuracy:P2}");
Console.WriteLine($"Auc: {metrics.Auc:P2}");
Console.WriteLine($"F1Score: {metrics.F1Score:P2}");
string modelFilePaht = Path.Combine(Environment.CurrentDirectory, @"Data\Model.zip");
using (var fs = new FileStream(modelFilePaht, FileMode.Create, FileAccess.Write, FileShare.Write))
{
mlContext.Model.Save(model, fs);
}
var prediction = mlContext.RunModel(model, "This was a very bad steak");
Console.WriteLine("\r\n--------------- Single Prediction with Trained Model ---------------");
Console.WriteLine($"This was a very bad steak. Prediction: {(Convert.ToBoolean(prediction.Prediction) ? "Positive" : "Negative")} | Probability: {prediction.Probability} ");
var sampleTexts = new[]
{
"This was a horrible meal",
"I love this spaghetti."
};
var predictions = mlContext.LoadAndRunModel(modelFilePaht, sampleTexts);
var textsAndPredictions = sampleTexts.Zip(predictions, (text, predition) => (text, prediction));
Console.WriteLine("\r\n--------------- Batch Prediction with Loaded Model ---------------");
foreach (var pair in textsAndPredictions)
{
Console.WriteLine($"{pair.text} | Prediction: {(Convert.ToBoolean(pair.prediction.Prediction) ? "Positive" : "Negative")} | Probability: {pair.prediction.Probability} ");
}
string lineText = Console.ReadLine();
while (lineText != "exit")
{
prediction = mlContext.RunModel(model, lineText);
Console.WriteLine($"{(Convert.ToBoolean(prediction.Prediction) ? "Positive" : "Negative")} | Probability: {prediction.Probability} ");
lineText = Console.ReadLine();
}
}
