public static List <SearchData> GenerateData(int count = 100)
{
var data = new List <SearchData>();
var rnd = new Random();
for (int i = 0; i < count; i++)
{
var newNode = new SearchData()
{
GroupId = rnd.Next(1, 5).ToString(), //nama yang di rating
Label = rnd.Next(0, 4), //rating 0-4
Features = rnd.Next(1, 100) //user atau identitas
};
data.Add(newNode);
}
return(data);
}
public static void Run()
{
MLContext mlContext = new MLContext();
// STEP 1: Load data
IDataView trainDataView = mlContext.Data.LoadFromEnumerable <SearchData>(GenerateData());
IDataView testDataView = mlContext.Data.LoadFromEnumerable <SearchData>(GenerateData(10));
// STEP 2: Run AutoML experiment
Console.WriteLine($"Running AutoML recommendation experiment for {ExperimentTime} seconds...");
ExperimentResult <RankingMetrics> experimentResult = mlContext.Auto()
.CreateRankingExperiment(new RankingExperimentSettings()
{
MaxExperimentTimeInSeconds = ExperimentTime
})
.Execute(trainDataView, testDataView,
new ColumnInformation()
{
LabelColumnName = LabelColumnName,
GroupIdColumnName = GroupColumnName
});
// STEP 3: Print metric from best model
RunDetail <RankingMetrics> bestRun = experimentResult.BestRun;
Console.WriteLine($"Total models produced: {experimentResult.RunDetails.Count()}");
Console.WriteLine($"Best model's trainer: {bestRun.TrainerName}");
Console.WriteLine($"Metrics of best model from validation data --");
PrintMetrics(bestRun.ValidationMetrics);
// STEP 5: Evaluate test data
IDataView testDataViewWithBestScore = bestRun.Model.Transform(testDataView);
RankingMetrics testMetrics = mlContext.Ranking.Evaluate(testDataViewWithBestScore, labelColumnName: LabelColumnName);
Console.WriteLine($"Metrics of best model on test data --");
PrintMetrics(testMetrics);
// STEP 6: Save the best model for later deployment and inferencing
mlContext.Model.Save(bestRun.Model, trainDataView.Schema, ModelPath);
// STEP 7: Create prediction engine from the best trained model
var predictionEngine = mlContext.Model.CreatePredictionEngine <SearchData, SearchDataPrediction>(bestRun.Model);
// STEP 8: Initialize a new test, and get the prediction
var testPage = new SearchData
{
GroupId = "1",
Features = 9,
Label = 1
};
var prediction = predictionEngine.Predict(testPage);
Console.WriteLine($"Predicted rating for: {prediction.Prediction}");
// New Page
testPage = new SearchData
{
GroupId = "2",
Features = 2,
Label = 9
};
prediction = predictionEngine.Predict(testPage);
Console.WriteLine($"Predicted: {prediction.Prediction}");
Console.WriteLine("Press any key to continue...");
Console.ReadKey();
}
