public static PredictionModel <NumberData, NumberPrediction> TrainModel(string trainingData)
{
Console.WriteLine("Training the model...");
var pipeline = new LearningPipeline();
TextLoader training = new TextLoader(trainingData);
pipeline.Add(training.CreateFrom <NumberData>(separator: ','));
pipeline.Add(new Dictionarizer("Label"));
pipeline.Add(new ColumnConcatenator("Features",
"b0",
"b1",
"b2",
"b3",
"b4",
"b5",
"b6",
"b7",
"b8",
"b9",
"b10",
"b11",
"b12",
"b13",
"b14",
"b15",
"b16",
"b17",
"b18",
"b19",
"b20",
"b21",
"b22",
"b23",
"b24",
"b25",
"b26",
"b27",
"b28",
"b29",
"b30",
"b31",
"b32",
"b33",
"b34",
"b35",
"b36",
"b37",
"b38",
"b39",
"b40",
"b41",
"b42",
"b43",
"b44",
"b45",
"b46",
"b47",
"b48",
"b49",
"b50",
"b51",
"b52",
"b53",
"b54",
"b55",
"b56",
"b57",
"b58",
"b59",
"b60",
"b61",
"b62",
"b63",
"b64",
"b65",
"b66",
"b67",
"b68",
"b69",
"b70",
"b71",
"b72",
"b73",
"b74",
"b75"));
pipeline.Add(new LogisticRegressionClassifier());
pipeline.Add(new PredictedLabelColumnOriginalValueConverter()
{
PredictedLabelColumn = "PredictedLabel"
});
var model = pipeline.Train <NumberData, NumberPrediction>();
Console.WriteLine("Done!");
return(model);
}
