我正在努力在ML.NET中对分类数据进行聚类。
var预测变量= mlContext.Model.CreatePredictionEngine(model)行失败,出现异常“ System.InvalidOperationException:'不兼容的功能列类型:'Vector'与'Vector'“
我刚接触ml,有人可以协助吗?
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
{
}
}
答案 0 :(得分:1)
我怀疑您看到了一些问题,因为如果您将onehotencoding和Trainer合并在一个管道中,那么您将管道分成两部分并以转换后的IDataView为基础进行实际培训,而无需成为管道的一部分管道,您可以简化代码:
<OrchestrationStep Order="5" Type="ClaimsExchange">
<ClaimsExchanges>
<ClaimsExchange Id="WriteLastLogonTime" TechnicalProfileReferenceId="Custom-TP-AAD-WriteLastLoginDateUsingObjectId" />
</ClaimsExchanges>
</OrchestrationStep>
它应该正常工作。