ml.net 中的分类数据聚类

Question

我正在为 ML.NET 中的分类数据聚类而苦苦挣扎。

var predictor = mlContext.Model.CreatePredictionEngine(model) 行失败并出现异常 "System.InvalidOperationException: 'Incompatible features column type: 'Vector' vs 'Vector''"

我对 ml 很陌生，有人可以帮忙吗？

谢谢！

class Program
{
    static void Main(string[] args)
    {
        var mlContext = new MLContext();
        var samples = new[]
        {
            new DataPoint {Education = "0-5yrs", ZipCode = "98005"},
            new DataPoint {Education = "0-5yrs", ZipCode = "98052"},
            new DataPoint {Education = "6-11yrs", ZipCode = "98005"},
            new DataPoint {Education = "6-11yrs", ZipCode = "98052"},
            new DataPoint {Education = "11-15yrs", ZipCode = "98005"}
        };

        IDataView data = mlContext.Data.LoadFromEnumerable(samples);

        var multiColumnKeyPipeline =
            mlContext.Transforms.Categorical.OneHotEncoding(
                new[]
                {
                    new InputOutputColumnPair("Education"),
                    new InputOutputColumnPair("ZipCode")
                });

        IDataView transformedData =
            multiColumnKeyPipeline.Fit(data).Transform(data);

        string featuresColumnName = "Features";
        var pipeline = mlContext.Transforms
            .Concatenate(featuresColumnName, "Education", "ZipCode")
            .Append(mlContext.Clustering.Trainers.KMeans(featuresColumnName, numberOfClusters: 2));
        var model = pipeline.Fit(transformedData);
        var predictor = mlContext.Model.CreatePredictionEngine<TransformedData, ClusterPredictionItem>(model);
    }

    private class DataPoint
    {
        public string Education { get; set; }

        public string ZipCode { get; set; }
    }

    private class TransformedData
    {
        public float Education { get; set; }

        public float ZipCode { get; set; }
    }
    internal class ClusterPredictionItem
    {
    }
}

Answer 1

我怀疑你看到了一些问题，因为你已经划分了你的管道并将你的实际训练基于来自转换的 IDataView 而不是管道的一部分，如果你合并你的 onehotencoding 和你的培训师在一个管道中，您可以简化代码：

 IDataView data = mlContext.Data.LoadFromEnumerable(samples);
        string featuresColumnName = "Features";
        var pipeline = mlContext.Transforms.Categorical.OneHotEncoding(
            new[]
            {
                new InputOutputColumnPair("Education"),
                new InputOutputColumnPair("ZipCode")
            }).Append(mlContext.Transforms.Concatenate("Features", "Education", "ZipCode"))
            .Append(mlContext.Clustering.Trainers.KMeans(featuresColumnName, numberOfClusters: 2));
        var model = pipeline.Fit(data);
        var predictor = mlContext.Model.CreatePredictionEngine<DataPoint, ClusterPredictionItem>(model);

它应该无一例外地工作。

ml.net 中的分类数据聚类

Clustering on categorical data in ml.net

c#

machine-learning

ml.net