Model Building Issues in Microsoft.ML

Question

I'm learning the Microsoft.ml framework, I tried to implement a simple model, but it produces very strange numbers. Tell me what I'm doing wrong:

    MLContext mlContext = new MLContext();

    IDataView trainingData = mlContext.Data.LoadFromEnumerable(data);

    var pipeline = mlContext.Transforms.Concatenate("Features", new[] {"R"})//, "R" 
        .Append(mlContext.Regression.Trainers.Sdca(labelColumnName: "P",  maximumNumberOfIterations: 1000));

    var model = pipeline.Fit(trainingData);

    var result = mlContext.Model.CreatePredictionEngine<EnterData, Prediction>(model).Predict(seachValue);

    return result;

The model is tuned for regression analysis of experimental data. I'm going to implement several network nodes, but for now I'm testing on a simple linear regression. In fact, the method should process the incoming data, train the model on it, make a prediction and return the answer to the test number.

The class wrapper is rolled out above. The problem is not in the message further down the code. There:

MessageBox.Show(result.P.ToString());

Answer 1

Buddy, Your question is not clear. What is your model type ? Sentiment Analysis, Facial Recognition or Cost Prediction?? Whatever, I think that the problem is issued in the last line of your code.

for example = return result.prediction();