[BugReport] Confusion Matrix doesn't appear as output artifact

[allinorcannon]

Describe the bug
After calling log_confusion_matrix only the test confusion matrix is shown in the charts section,while nothing is shown in the output artifacts section (Screenshots provided in the appropriate section).
When using aws-cli all three of the confusion matrices generated by the code are visible, as on the s3, so this is not a code issue. I believe this is a bug, since it clearly states in the documentation of the function that the 'is_output' argument ensures that the confusion_matrix is depicted as an output artifact.
To reproduce
Train a model in sagemaker within an experiments run context, use the log_confusion_matrix and wait for the results.
Expected behavior
Confusion matrices should be available as output artifacts via the Sagemaker Studio UI
Screenshots or logs


System information
A description of your system. Please provide:

• SageMaker Python SDK version: 2.199.0
• Framework name (eg. PyTorch) or algorithm (eg. KMeans): PyTorch
• Framework version: 2.0.1
• Python version: Python 3.10.6
• CPU or GPU: GPU
• Custom Docker image (Y/N): Y
  Additional context
  Another thing would be the possibility of seeing all confusion matrices - it would be very useful and a quick adjustment since they are generated to s3 either way.

[Gajam-Anurag]

Thank you for reporting this issue. We recognize that you are using SageMaker Experiments, which is currently in maintenance mode. For optimal experiment tracking capabilities, we recommend migrating to our newer MLflow integration with Amazon SageMaker, which offers enhanced features and continued active development. You can find detailed migration guidance in our documentation at https://docs.aws.amazon.com/sagemaker/latest/dg/experiments.html#experiments-mlflow-migration.