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Message type: E = Error
Message class: RSDME -
Message number: 953
Message text: Invalid value for prediction parameter &1( &2 )
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RSDME953
- Invalid value for prediction parameter &1( &2 ) ?The SAP error message RSDME953, which states "Invalid value for prediction parameter &1 ( &2 )", typically occurs in the context of SAP BW (Business Warehouse) when working with predictive analytics or data mining functionalities. This error indicates that a parameter value provided for a prediction model is not valid or acceptable.
Cause:
Invalid Parameter Value: The parameter specified (denoted by &1) is not within the expected range or format. This could be due to:
- Typographical errors in the parameter value.
- Using a value that is not supported by the predictive model.
- Missing required parameters.
Model Configuration Issues: The predictive model may not be properly configured, leading to invalid parameter settings.
Data Type Mismatch: The value provided may not match the expected data type for the parameter.
Version Compatibility: There may be compatibility issues between the version of the predictive model and the data being used.
Solution:
Check Parameter Values: Review the values being passed for the prediction parameters. Ensure they are valid and conform to the expected formats and ranges.
Review Model Configuration: Verify the configuration of the predictive model. Ensure that all required parameters are set correctly and that optional parameters are not causing conflicts.
Consult Documentation: Refer to the SAP documentation for the specific predictive model you are using. This can provide insights into valid parameter values and configurations.
Data Type Verification: Ensure that the data types of the parameters match what is expected by the model. For example, if a parameter expects a numeric value, ensure that a string or other type is not being passed.
Update or Patch: If the issue is related to version compatibility, check for any updates or patches for your SAP BW system that may resolve the issue.
Testing: If possible, test the predictive model with known valid parameters to isolate the issue.
Related Information:
By following these steps, you should be able to identify the cause of the RSDME953 error and implement a solution to resolve it.
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