System.ArgumentOutOfRangeException: '未找到特征列 'Feature'（参数 'schema'）'

Question

我在训练模型时遇到问题。我有一系列 HTTP 请求，我希望能够确定请求是否来自机器人。为了训练这个，我有一系列的这些：

public class Request
{
    public string Url { get; set; }
    public string UserAgent { get; set; }
    public bool IsBot { get; set; }
}

预测 class 是这样的：

public class IsBotPrediction
{
    [ColumnName("PredictedLabel")]
    public bool Prediction { get; set; }
    public float Score { get; set; }
}

为了这个例子，我创建了一个硬编码数据列表：

var trainingData = new List<Request>
{
    new Request { Url = "/wp-admin", UserAgent = "a bot", IsBot = true },
    new Request { Url = "/backoffice", UserAgent = "a bot", IsBot = true },
    new Request { Url = "/hack", UserAgent = "a bot", IsBot = true },
    new Request { Url = "/login", UserAgent = "a bot", IsBot = false },
    new Request { Url = "/dashboard", UserAgent = "a bot", IsBot = false },
    new Request { Url = "/humans.txt", UserAgent = "a bot", IsBot = false },
    new Request { Url = "/admin", UserAgent = "a bot", IsBot = true },
};

为了训练模型，我使用了以下代码：

IDataView mlData = mlContext.Data.LoadFromEnumerable(trainingData);

var dataPrepPipeline = mlContext
    .Transforms
    .Text
    .FeaturizeText("UrlF", "Url")
    .Append(mlContext.Transforms.Text.FeaturizeText("UserAgentF", "UserAgent"))
    .Append(mlContext.Transforms.Concatenate("Features", "UrlF", "UserAgentF"))
    .Append(mlContext.Transforms.NormalizeMinMax("Features", "Features"))
    .AppendCacheCheckpoint(mlContext);
var prepPipeline = dataPrepPipeline.Fit(mlData);

var trainer = mlContext
    .BinaryClassification
    .Trainers
    .AveragedPerceptron(labelColumnName: "IsBot", numberOfIterations: 10, featureColumnName: "Features");

var preprocessedData = prepPipeline.Transform(mlData);

ITransformer trainedModel = trainer.Fit(preprocessedData);

训练好的模型似乎成功了。但是当我尝试创建预测引擎时：

var predEngine = mlContext.Model.CreatePredictionEngine<Request, IsBotPrediction>(trainedModel);

我得到以下异常：

System.ArgumentOutOfRangeException: 'Features column 'Feature' not found (Parameter 'schema')'

你能帮我看看这是什么意思吗？

Answer 1

这可能是由于在将数据拟合到模型之前对数据进行了转换。

以下设置应该有效。

var dataPrepPipeline = mlContext.Transforms.Text.FeaturizeText("UrlF", "Url")
     .Append(mlContext.Transforms.Text.FeaturizeText("UserAgentF", "UserAgent"))
     .Append(mlContext.Transforms.Concatenate("Features", "UrlF", "UserAgentF"))
     .Append(mlContext.Transforms.NormalizeMinMax("Features", "Features"))
     .AppendCacheCheckpoint(mlContext);

var dataPrepModel = dataPrepPipeline.Fit(mlData);
var dataPrepDataView = dataPrepModel.Transform(mlData);

var pipeline = dataPrepPipeline.Append(
            mlContext.BinaryClassification.Trainers.AveragedPerceptron(labelColumnName: "IsBot", numberOfIterations: 10, featureColumnName: "Features"));

mlContext.Model.Save(dataPrepModel, dataPrepDataView.Schema, "./dataprep.zip");

var model = pipeline.Fit(mlData);

var modelDataView = model.Transform(mlData);

mlContext.Model.Save(model, modelDataView.Schema, "./model.zip");

var predEngine = mlContext.Model.CreatePredictionEngine<Request, IsBotPrediction>(model);

System.ArgumentOutOfRangeException: '未找到特征列 'Feature'（参数 'schema'）'

System.ArgumentOutOfRangeException: 'Features column 'Feature' not found (Parameter 'schema')'

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