Data Classification unable to train

**System Information (please complete the following information):**
Model Builder Version 17.18.2.2415501
VS 2022 Version 17.9.2

**Describe the bug**
training
fails to train with example provided in Microsoft ML Net tutorial Data Classification ML

**To Reproduce**
Steps to reproduce the behavior:
1. Create new console application
2. Create csv file with this data SepalLength SepalWidth Petal Length Petal Width Species
5.1 3.5 1.4 0.2 setosa (provided https://learn.microsoft.com/en-us/dotnet/machine-learning/automate-training-with-model-builder#data))
3. Save training file to application folder
4. Add new ML config file
5. Browse to the created training file
6. Select Species as Label
7. Click Next Step
8. Click Train
9. See Error Schema mismatch for score column 'Score': expected vector of two or more items of type Single, got Vector
Parameter name: schema

**Expected behavior**
This model should train (as provided)

**Additional context**
Also tried a four row CVS file with this data.
Temperature,Humidity,Dewpoint,Windspeed,Visibility,Alert
0.0,45.0,0.0,0.0,0.0,frost
5.0,45.0,5.0,0.0,0.0,dew
5.0,45.0,7.0,0.0,0.0,none
Same error received on training using this data.

Reproduziere den Fehler in Model Builder 17.18.2.2415501 anhand der verlinkten ML.NET Data Classification-Tutorialdaten und des kleineren CSV-Beispiels. Prüfe zunächst, wie das ausgewählte Species- oder Alert-Label abgeleitet wird und wo die gemeldete Abweichung im Score-Schema auftritt. Erledigt ist dies, wenn beide Datensätze das Training ohne den Vektorgrößenfehler abschließen.

Vom Indexierungsmodell aus dem Issue-Text verfasst.