How To Fix RSDME322 - Specified model fields not sufficient for training

SAP Error Message - Details

• Message type: E = Error

• Message class: RSDME -

• Message number: 322

• Message text: Specified model fields not sufficient for training

What causes this issue?

There is no model field that can be used for training.

System Response

The system issues an error message and will not allow you to continue with this transaction until the error is resolved.

How to fix this error?

Other than the model keys and predictable field, also specify at least
one CONTINUOUS type model column or at least two ORDERED/DISCRETE type
model fields for training.

Procedure for System Administrators

Error message extract from SAP system. Copyright SAP SE.

Smart SAP Assistant

• What is the cause and solution for SAP error message RSDME322 - Specified model fields not sufficient for training ?

  The SAP error message RSDME322, which states "Specified model fields not sufficient for training," typically occurs in the context of SAP BW (Business Warehouse) or SAP BW/4HANA when you are trying to create or train a predictive model using the SAP Predictive Analytics or SAP BW Integrated Planning functionalities. This error indicates that the fields you have selected for the model do not provide enough information or variability for the training process.
  Causes:
  
  Insufficient Data: The selected fields may not have enough data points or variability. For example, if the fields contain too many null values or if the data is not diverse enough, the model cannot learn effectively.
  Field Types: The fields selected may not be appropriate for the type of model you are trying to create. For instance, categorical fields may not be suitable for certain types of predictive models.
  Data Quality Issues: Poor data quality, such as duplicates, inconsistencies, or incorrect data types, can lead to this error.
  Inadequate Number of Features: If the number of features (fields) is too low, the model may not have enough information to make predictions.
  
  Solutions:
  
  Review Selected Fields: Check the fields you have selected for the model. Ensure that they are relevant and provide sufficient variability. Consider adding more fields that may contribute to the model's predictive power.
  Data Cleansing: Clean the data to remove null values, duplicates, and inconsistencies. Ensure that the data types are correct and that the data is formatted properly.
  Increase Data Volume: If possible, increase the volume of data used for training. More data can help the model learn better.
  Feature Engineering: Create new features that may help improve the model's performance. This could involve combining existing fields or deriving new metrics from the data.
  Check Model Configuration: Ensure that the model configuration settings are appropriate for the type of analysis you are performing. This includes checking the algorithm settings and ensuring they align with the data characteristics.
  
  Related Information:
  
  SAP Documentation: Refer to the official SAP documentation for guidance on predictive modeling and data preparation best practices.
  SAP Community: Engage with the SAP Community forums to seek advice from other users who may have encountered similar issues.
  Training and Tutorials: Consider taking training courses or tutorials on SAP BW and predictive analytics to better understand how to prepare data and configure models effectively.
  
  By addressing the underlying causes and implementing the suggested solutions, you should be able to resolve the RSDME322 error and successfully train your predictive model.