#r "nuget:Microsoft.ML"
#r "nuget:Microsoft.ML.LightGbm"
#r "nuget:Microsoft.ML.FastTree"
using System;
using System.Linq;
using Microsoft.ML;
using Microsoft.ML.Data;
public class ModelInput
{
public float Feature1 { get; set; }
public float Feature2 { get; set; }
public bool Label { get; set; }
}
// Create a new MLContext
var mlContext = new MLContext();
// Define the training data schema
var data = new[]
{
new ModelInput { Feature1 = 1f, Feature2 = 2f, Label = true },
new ModelInput { Feature1 = 3f, Feature2 = 4f, Label = false },
new ModelInput { Feature1 = 5f, Feature2 = 6f, Label = true },
new ModelInput { Feature1 = 7f, Feature2 = 8f, Label = false },
new ModelInput { Feature1 = 9f, Feature2 = 10f, Label = true }
};
// Load the training data
var trainData = mlContext.Data.LoadFromEnumerable(data);
// Define the LightGBM binary classification trainer
var trainer = mlContext.BinaryClassification.Trainers.FastForest();
// Train the model
var pipeline = mlContext.Transforms.Concatenate("Features", nameof(ModelInput.Feature1), nameof(ModelInput.Feature2))
.Append(trainer);
var model = pipeline.Fit(trainData);
// Define new data points for prediction
var newData = new[]
{
new ModelInput { Feature1 = 2f, Feature2 = 3f },
new ModelInput { Feature1 = 4f, Feature2 = 5f },
new ModelInput { Feature1 = 6f, Feature2 = 7f },
new ModelInput { Feature1 = 8f, Feature2 = 9f },
new ModelInput { Feature1 = 10f, Feature2 = 11f }
};
// Load the new data
var newDataView = mlContext.Data.LoadFromEnumerable(newData);
// Make predictions on the new data
var transformedNewData = model.Transform(newDataView);
// Extract the Probability column
var probabilities = transformedNewData.GetColumn<float>("Probability").ToArray();
// Extract the Feature1 and Feature2 columns
var feature1 = newData.Select(x => x.Feature1).ToArray();
var feature2 = newData.Select(x => x.Feature2).ToArray();
// Print the Probability scores for each prediction
for (int i = 0; i < probabilities.Length; i++)
{
Console.WriteLine($"Feature1: {feature1[i]}, Feature2: {feature2[i]}, Probability: {probabilities[i]}");
}
why no Probability?
polyglot vscode c# notebook:
Error: System.ArgumentOutOfRangeException: Column 'Probability' not found (Parameter 'name')
at Microsoft.ML.DataViewSchema.get_Item(String name)
at Microsoft.ML.Data.ColumnCursorExtensions.GetColumn[T](IDataView data, String columnName)
at Submission#18.<>d__0.MoveNext()
--- End of stack trace from previous location ---
at Microsoft.CodeAnalysis.Scripting.ScriptExecutionState.RunSubmissionsAsync[TResult](ImmutableArray
1 precedingExecutors, Func2 currentExecutor, StrongBox1 exceptionHolderOpt, Func2 catchExceptionOpt, CancellationToken cancellationToken)Documentation says yes have probability. why not have?