How To Fix RSDME325 - Tree info : Trial &1 ; Sampled Recs &2 ; Accuracy &3

SAP Error Message - Details

• Message type: E = Error

• Message class: RSDME -

• Message number: 325

• Message text: Tree info : Trial &1 ; Sampled Recs &2 ; Accuracy &3

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 RSDME325 - Tree info : Trial &1 ; Sampled Recs &2 ; Accuracy &3 ?

  The SAP error message RSDME325 typically relates to issues encountered during the execution of a data mining or predictive analysis task in SAP BW (Business Warehouse) or SAP HANA. This error message indicates a problem with the tree information, specifically regarding the trial, sampled records, and accuracy of a model.
  Cause:
  
  Insufficient Data: The model may not have enough data to generate a reliable tree structure, leading to issues with accuracy.
  Data Quality Issues: Poor quality data, such as missing values or outliers, can affect the model's ability to create a valid decision tree.
  Configuration Issues: Incorrect settings in the data mining configuration or parameters may lead to this error.
  Model Complexity: The model may be too complex for the available data, resulting in overfitting or underfitting.
  
  Solution:
  
  Check Data Quality: Ensure that the data being used for the model is clean, complete, and relevant. Address any missing values or outliers.
  Increase Sample Size: If possible, increase the amount of data being used for training the model to improve its reliability.
  Review Configuration: Check the settings and parameters used in the data mining process. Ensure they are appropriate for the data and the analysis being performed.
  Simplify the Model: If the model is too complex, consider simplifying it or using a different algorithm that is more suited to the available data.
  Run Diagnostics: Use any available diagnostic tools in SAP to analyze the model and identify specific issues that may be causing the error.
  
  Related Information:
  
  SAP Notes: Check SAP Notes for any known issues or patches related to this error message. SAP frequently updates its documentation and provides fixes for known problems.
  Documentation: Review the SAP BW or SAP HANA documentation for best practices in data mining and predictive analysis.
  Community Forums: Engage with the SAP community forums or support channels to see if other users have encountered similar issues and what solutions they found effective.
  
  If the problem persists after trying these solutions, it may be beneficial to reach out to SAP support for further assistance.