MLNetAutoMLAPIConsole.cs
private const uint ExperimentTime = 180; | |
static void Main(string[] args) | |
{ | |
var mlContext = new MLContext(); | |
Train(mlContext); | |
Console.WriteLine("Process complete! Press any key to close the app."); | |
Console.ReadKey(); | |
} | |
public static void Train(MLContext mlContext) | |
{ | |
try | |
{ | |
// STEP 1: Load the data | |
var trainData = mlContext.Data.LoadFromTextFile(path: "AgeRangeData03_AgeGenderLabelEncodedMoreData.csv", | |
columns: new[] | |
{ | |
new TextLoader.Column("Age", DataKind.Single, 0), | |
new TextLoader.Column("Gender", DataKind.Single, 1) | |
, | |
new TextLoader.Column("Label", DataKind.Single, 2) | |
}, | |
hasHeader: true, | |
separatorChar: ',' | |
); | |
var progressHandler = new MulticlassExperimentProgressHandler(); | |
ConsoleHelper.ConsoleWriteHeader("=============== Running AutoML experiment ==============="); | |
Console.WriteLine($"Running AutoML multiclass classification experiment for {ExperimentTime} seconds..."); | |
ExperimentResult<MulticlassClassificationMetrics> experimentResult = mlContext.Auto() | |
.CreateMulticlassClassificationExperiment(ExperimentTime) | |
.Execute(trainData, "Label", progressHandler: progressHandler); | |
// Print top models found by AutoML | |
Console.WriteLine(); | |
PrintTopModels(experimentResult); | |
Console.WriteLine(); | |
} | |
catch (Exception ex) | |
{ | |
Console.WriteLine(ex); | |
} | |
} |
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