我正在尝试使用新的Microsoft.ML 0.6.0进行预测功能

当我调用“ model.AsDynamic.MakePredictionFunction”时,我收到


  “ System.ArgumentOutOfRangeException:'无法确定IDataView
  成员特征的类型”。


码:

using System;
using Microsoft.ML;
using Microsoft.ML.Runtime.Api;
using Microsoft.ML.Runtime.Data;
using Microsoft.ML.Trainers;
using Microsoft.ML.StaticPipe;

namespace MachineLearning
{
    class MLTest
    {
        public void Run()
        {
            var env = new LocalEnvironment();
            var reader = TextLoader.CreateReader(env, ctx => (label: ctx.LoadBool(0), features: ctx.LoadFloat(1, 3)));
            var traindata = reader.Read(new MultiFileSource("train.txt"));
            var bctx = new BinaryClassificationContext(env);
            var est = reader.MakeNewEstimator()
                .Append(x => (x.label, prediction: bctx.Trainers.Sdca(x.label, x.features.Normalize())));
            var model = est.Fit(traindata);

            //FAILS: System.ArgumentOutOfRangeException: 'Could not determine an IDataView type for member features'
            var predictionFunct = model.AsDynamic.MakePredictionFunction<Issue, Prediction>(env);

        }

        public class Issue
        {
            public float label;
            public Vector<float> features; //what is wrong?
        }

        public class Prediction
        {
            [ColumnName("prediction.predictedLabel")]
            public bool PredictionLabel;

            [ColumnName("prediction.probability")]
            public float Probability;

            [ColumnName("prediction.score")]
            public float Score;
        }
    }
}


文件train.txt包含:

1   0   0   0
1   0   1   0
1   0   0   1
1   0   1   1
0   1   1   1
0   1   0   1
0   1   1   0
0   1   0   0


看起来好像是“问题”类中的错误,但是究竟是什么错误呢?谢谢

最佳答案

您正在尝试schema comprehension to make a dataview and to read。通过使用基本数组,可以使用columntype设置数组的大小。

(这是针对ML.NET版本.10的)

public class Issue
{
        public float label;
        public float[] features; //change this
}


Using SchemaDefinition for run-time type mapping hints

var inputSchemaDefinition = SchemaDefinition.Create(typeof(Issue), SchemaDefinition.Direction.Both);
inputSchemaDefinition["features"].ColumnType = new VectorType(NumberType.R4, 4);


然后,您将创建引擎:

var predictionEngine = model.CreatePredictionEngine<InputSchema, Prediction>(model as IHostEnvironment, inputSchemaDefinition, outputSchemaDefinition);

10-07 23:38