How To Fix MDQ_ML_ADAPTER003 - Rule mining does not support the given data selection sign.

MDQ_ML_ADAPTER003 - Overview

• Message type: E = Error

• Message class: MDQ_ML_ADAPTER - Message Class for CX_MDQ_ML_ADAPTER

• Message number: 003

• Message text: Rule mining does not support the given data selection sign.

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 MDQ_ML_ADAPTER003 - Rule mining does not support the given data selection sign. ?

  The SAP error message MDQ_ML_ADAPTER003 indicates that there is an issue with the data selection criteria used in a rule mining process. This error typically arises when the data selection sign (e.g., operators like '=', '<', '>', etc.) used in the selection criteria is not supported by the rule mining functionality in SAP.
  
  Cause:
  
  Unsupported Operators: The error is often caused by using operators in the data selection that are not compatible with the rule mining algorithm. For example, using a 'greater than' or 'less than' operator when the algorithm expects equality checks.
  Data Type Mismatch: The data types of the fields being compared may not be compatible with the operators being used.
  Incorrect Configuration: The configuration of the rule mining process may not align with the data model or the expected input format.
  
  
  Solution:
  
  Review Data Selection Criteria: Check the data selection criteria used in the rule mining process. Ensure that only supported operators are