How To Fix RSANA_UMM_API091 - Model Training was unsuccessful

SAP Error Message - Details

• Message type: E = Error

• Message class: RSANA_UMM_API - UMM API Messages

• Message number: 091

• Message text: Model Training was unsuccessful

Self-Explanatory Message

Since SAP believes that this specific error message is 'self-explanatory,' no more information has been given.The majority of messages in the SAP system have a message text, however this is frequently insufficient to comprehend or resolve the problem.

To make things easier, more detailed information is frequently added to describe the issue, how to fix it, and the necessary steps or configuration modifications.

Unfortunately, there isn't any extra information in this error notice.

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Smart SAP Assistant

• What is the cause and solution for SAP error message RSANA_UMM_API091 - Model Training was unsuccessful ?

  The SAP error message RSANA_UMM_API091, which indicates that "Model Training was unsuccessful," typically arises in the context of SAP Analytics Cloud (SAC) or SAP BW/4HANA when there are issues during the training of a predictive model. Here are some common causes, potential solutions, and related information:
  Causes:
  
  Data Quality Issues: The dataset used for training may contain missing values, outliers, or incorrect data types that can hinder the model's ability to learn effectively.
  Insufficient Data: The dataset may not have enough records or variability to train a robust model.
  Feature Selection: The features selected for training may not be relevant or may not have enough predictive power.
  Configuration Errors: Incorrect settings in the model configuration, such as parameters for the training algorithm, can lead to failure.
  Resource Limitations: Insufficient computational resources (memory, processing power) can cause the training process to fail.
  Version Compatibility: There may be compatibility issues between different versions of SAP components or libraries.
  
  Solutions:
  
  Data Cleaning: Review and clean the dataset to handle missing values, outliers, and ensure correct data types. Use techniques like imputation for missing values.
  Increase Dataset Size: If possible, augment the dataset with more records or features that can provide additional context for the model.
  Feature Engineering: Analyze the features being used and consider adding or removing features based on their relevance and importance.
  Review Configuration Settings: Double-check the model configuration settings to ensure they are appropriate for the data and the problem being solved.
  Monitor Resource Usage: Ensure that the system has adequate resources available for model training. Consider optimizing the environment or using a more powerful instance if necessary.
  Check Logs for Errors: Review the logs or error messages generated during the training process for more specific information about what went wrong.
  Update Software: Ensure that you are using the latest version of SAP components and libraries, as updates may contain bug fixes and improvements.
  
  Related Information:
  
  Documentation: Refer to the official SAP documentation for predictive analytics and model training for specific guidelines and best practices.
  SAP Community: Engage with the SAP Community forums to seek advice from other users who may have encountered similar issues.
  SAP Support: If the issue persists, consider reaching out to SAP Support for assistance, providing them with detailed logs and error messages for better troubleshooting.
  
  By addressing the potential causes and implementing the suggested solutions, you should be able to resolve the RSANA_UMM_API091 error and successfully train your predictive model.