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How To Fix VCH_HL_ENG_PROCESSOR118 - Model rolled back to iteration index.


SAP Error Message - Details

  • Message type: E = Error

  • Message class: VCH_HL_ENG_PROCESSOR - Messages related to validation

  • Message number: 118

  • Message text: Model rolled back to iteration index.

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  • 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.



    What else can you do?

    First, use our AnswerBot below to get a possible cause and solution (requires a premium subscription).

    Also, review the in-depth Common Questions & Answers listed below; you could discover a solution there or be able to connect with others who have faced similar challenges.

    You can also try searching the SAP support portal (support.sap.com) but you need a special user ID to access it. It is possible that an SAP support note exists that provides additional details about the mistake or even steps for fixing it.


Smart SAP Assistant

  • What is the cause and solution for SAP error message VCH_HL_ENG_PROCESSOR118 - Model rolled back to iteration index. ?

    The SAP error message "VCH_HL_ENG_PROCESSOR118 Model rolled back to iteration index" typically occurs in the context of SAP's advanced analytics or machine learning functionalities, particularly when using the SAP HANA platform or SAP Analytics Cloud. This error indicates that a model training process has encountered an issue that necessitated a rollback to a previous iteration of the model.

    Causes:

    1. Data Quality Issues: The input data may contain anomalies, such as missing values, outliers, or incorrect data types, which can lead to instability during model training.
    2. Model Configuration: Incorrect or suboptimal hyperparameters or model configurations can cause the training process to fail or produce invalid results.
    3. Resource Limitations: Insufficient computational resources (CPU, memory) can lead to failures during the training process.
    4. Algorithmic Instability: Some algorithms may be sensitive to the data or configuration, leading to convergence issues or instability during training.
    5. Version Compatibility: Using incompatible versions of SAP components or libraries can lead to unexpected behavior.

    Solutions:

    1. Data Validation: Check the input data for quality issues. Clean the data by handling missing values, removing outliers, and ensuring that data types are correct.
    2. Adjust Model Parameters: Review and adjust the hyperparameters of the model. Consider using default settings or performing hyperparameter tuning to find a more stable configuration.
    3. Increase Resources: If resource limitations are suspected, consider increasing the computational resources allocated to the model training process.
    4. Review Logs: Check the logs for more detailed error messages or warnings that can provide insights into what went wrong during the training process.
    5. Update Software: Ensure that you are using the latest versions of SAP components and libraries. Check for any patches or updates that may address known issues.
    6. Consult Documentation: Refer to the official SAP documentation for guidance on the specific model or algorithm you are using, as it may provide insights into common issues and best practices.

    Related Information:

    • SAP Community: Engage with the SAP Community forums to see if other users have encountered similar issues and what solutions they found effective.
    • SAP Notes: Search for relevant SAP Notes in the SAP Support Portal that may address this specific error or provide additional troubleshooting steps.
    • Training and Resources: Consider taking advantage of SAP training resources or tutorials that cover best practices for data preparation and model training.

    If the issue persists after trying the above solutions, it may be beneficial to reach out to SAP support for further assistance, providing them with detailed information about the error and the context in which it occurred.

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