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Message type: E = Error
Message class: RSDME -
Message number: 542
Message text: Required clusters reset equal to training data size (&1)
The number of valid data records in the training data is less than the
requested number of clusters.
The number of clusters is reset to the size of the training data.
If the training results are not satisfactory, increase the training
data size by using a suitable query.
The system issues an error message and will not allow you to continue with this transaction until the error is resolved.
Error message extract from SAP system. Copyright SAP SE.
RSDME542
- Required clusters reset equal to training data size (&1) ?The SAP error message RSDME542 indicates that there is a mismatch between the required number of clusters for a certain operation and the size of the training data. This error typically occurs in the context of SAP BW (Business Warehouse) or SAP HANA when working with data modeling, especially in scenarios involving data mining or predictive analytics.
Cause:
The error message "Required clusters reset equal to training data size (&1)" usually arises due to one of the following reasons:
Insufficient Data: The training data set may not have enough records to create the required number of clusters. This can happen if the data is filtered too much or if there are not enough relevant records in the dataset.
Configuration Issues: The settings for the clustering algorithm may be incorrectly configured, leading to a requirement for more clusters than can be supported by the available data.
Data Quality Issues: If the data contains a lot of missing values or outliers, it may not be suitable for clustering, which can lead to this error.
Solution:
To resolve the RSDME542 error, you can take the following steps:
Check Data Size: Ensure that the training dataset has enough records. If the dataset is too small, consider using a larger dataset or aggregating data from multiple sources.
Adjust Clustering Parameters: Review the parameters set for the clustering algorithm. You may need to reduce the number of clusters required or adjust other settings to better fit the available data.
Data Quality Improvement: Clean the dataset by handling missing values, removing outliers, and ensuring that the data is relevant and well-structured for clustering.
Re-run the Process: After making the necessary adjustments, re-run the clustering process to see if the error persists.
Consult Documentation: Refer to SAP documentation or support resources for specific guidance on the clustering algorithm you are using, as different algorithms may have different requirements.
Related Information:
By following these steps, you should be able to diagnose and resolve the RSDME542 error effectively.
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