安装导致 Ml.net 异常的管道。这Fit
不是一个等待的事情,我很困惑为什么会发生这种情况。任何帮助都是值得赞赏的
var model = pipeline.Fit(dataView);
堆栈跟踪
在
System.Threading.Channels.AsyncOperation.ThrowIncompleteOperationException()
在 System.Threading.Channels.AsyncOperation1.GetResult(Int16 token) at Microsoft.ML.Transforms.RowShufflingTransformer.Cursor.MoveNextCore() at Microsoft.ML.Data.RootCursorBase.MoveNext() at Microsoft.ML.Trainers.TrainingCursorBase.MoveNext() at Microsoft.ML.Trainers.SdcaTrainerBase
3.TrainCore(IChannel ch,
RoleMappedData 数据、LinearModelParameters 预测器、Int32
重量集计数)在
Microsoft.ML.Trainers.StochasticTrainerBase2.TrainModelCore(TrainContext context) at Microsoft.ML.Trainers.TrainerEstimatorBase
2.TrainTransformer(IDataView
trainSet、IDataView 验证集、IPredictor initPredictor) at
Microsoft.ML.Trainers.TrainerEstimatorBase2.Fit(IDataView input) at Microsoft.ML.Data.EstimatorChain
1.Fit(IDataView输入)在
ML.DetectFakeJobPosts.Analyzer.Train() 中
D:\Sources\code-everything\CodeItHere\ML.DetectFakeJobPosts\Program.cs:line
75 在 ML.DetectFakeJobPosts.Program.Main(String[] args) 中
D:\Sources\code-everything\CodeItHere\ML.DetectFakeJobPosts\Program.cs:line
13
Pipeline
var pipeline = _context.Transforms.Categorical.OneHotEncoding("ec_title", "title")
.Append(_context.Transforms.Categorical.OneHotEncoding("ec_location", "location"))
.Append(_context.Transforms.Categorical.OneHotEncoding("ec_department", "department"))
.Append(_context.Transforms.Categorical.OneHotEncoding("ec_salary_range", "salary_range"))
.Append(_context.Transforms.Text.FeaturizeText("ec_company_profile", "company_profile"))
.Append(_context.Transforms.Text.FeaturizeText("ec_description", "description"))
.Append(_context.Transforms.Text.FeaturizeText("ec_requirements", "requirements"))
.Append(_context.Transforms.Text.FeaturizeText("ec_benefits", "benefits"))
.Append(_context.Transforms.Categorical.OneHotEncoding("ec_employment_type", "employment_type"))
.Append(_context.Transforms.Categorical.OneHotEncoding("ec_required_experience", "required_experience"))
.Append(_context.Transforms.Categorical.OneHotEncoding("ec_required_education", "required_education"))
.Append(_context.Transforms.Categorical.OneHotEncoding("ec_industry", "industry"))
.Append(_context.Transforms.Categorical.OneHotEncoding("ec_function", "function"))
//drop unnecessary columns from view
.Append(_context.Transforms.DropColumns("title", "location", "department", "salary_range", "company_profile", "description", "requirements", "benefits", "employment_type", "required_experience", "required_education", "industry", "function", "telecommuting", "has_company_logo", "has_questions"))
//concate features
.Append(_context.Transforms.Concatenate("Features", "ec_title", "ec_location", "ec_department", "ec_salary_range", "ec_company_profile", "ec_description", "ec_requirements", "ec_benefits", "ec_employment_type", "ec_required_experience", "ec_required_education", "ec_industry", "ec_function"))
//set label/prediction column
.Append(_context.Transforms.Conversion.ConvertType("Label", "fraudulent", DataKind.Boolean))
//select a trainer
.Append(_context.BinaryClassification.Trainers.SdcaLogisticRegression());
单击此处获取数据集 https://www.kaggle.com/shivamb/real-or-fake-fake-jobposting-prediction
Versions
ML.net:1.5.1
核心:3.1