ML.NET如何使输入模型泛型？

using Microsoft.ML;
using Microsoft.ML.Data;
using System;
using System.Collections.Generic;

// 定义输入数据的模型
public class InputData
{
    public float Feature1 { get; set; }
    public float Feature2 { get; set; }
}

// 定义输出数据的模型
public class OutputData
{
    public bool Prediction { get; set; }
}

class Program
{
    static void Main(string[] args)
    {
        // 创建MLContext对象
        var context = new MLContext();

        // 创建一个包含输入数据的泛型列表
        var inputData = new List<InputData>()
        {
            new InputData() { Feature1 = 1.0f, Feature2 = 2.0f },
            new InputData() { Feature1 = 3.0f, Feature2 = 4.0f },
            new InputData() { Feature1 = 5.0f, Feature2 = 6.0f }
        };

        // 将泛型列表加载到IDataView中
        var dataView = context.Data.LoadFromEnumerable(inputData);

        // 创建机器学习管道
        var pipeline = context.Transforms.Conversion.MapValueToKey("Label")
            .Append(context.Transforms.Concatenate("Features", "Feature1", "Feature2"))
            .Append(context.Transforms.NormalizeMinMax("Features"))
            .Append(context.Transforms.Conversion.MapKeyToValue("Label"))
            .Append(context.Transforms.Conversion.MapKeyToValue("PredictedLabel"))
            .Append(context.Transforms.Conversion.MapValueToKey("PredictedLabel"));

        // 训练模型
        var model = pipeline.Fit(dataView);

        // 使用模型进行预测
        var predictionEngine = context.Model.CreatePredictionEngine<InputData, OutputData>(model);
        var prediction = predictionEngine.Predict(new InputData() { Feature1 = 7.0f, Feature2 = 8.0f });

        Console.WriteLine($"预测结果：{prediction.Prediction}");
    }
}