Have you tried ML.NET?
It's a new machine learning framework made specifically for .NET developers.

ML.NET Tutorial - Get started in 10 minutes

Evaluate your model

The Evaluate step shows you the best-performing algorithm and the best accuracy and lets you try out the model in the UI.

Try out your model

You can make predictions on sample input in the Try your model section. The textbox is pre-filled with the first line of data from your dataset, but you can change the input and hit Predict to try out different Sentiment predictions.

In this case, 1 means negative sentiment and 0 means positive sentiment.

After evaluating and trying out your model, move on to the Code step.

After the ML.NET CLI selects the best model, it will display the training Summary, which shows you a summary of the exploration process, including how many models were explored in the given training time.

Top models

While the ML.NET CLI generates code for the highest performing model, it also displays the top models (up to 5) with the highest accuracy that it found in the given exploration time. It displays several evaluation metrics for those top models, including AUC, AUPRC, and F1-score. For more information, see ML.NET metrics.