Assume that you use the PREDICT or sp_rxPredict function in SQL Server 2017 ML Services in the following scenarios:
When you use the PREDICT function to generate predicated values or scores based on a rxDTree, rxDForest, or rxBTrees model, and the columns that are needed to make the prediction are missing from the input data of the WITH clause, the execution would fail without a detailed error message that states which column is missing.
Learning rate in the tree models (rxDtree, rxBtrees, and rxDforest) was not included in the serialized real-time model. Therefore, a default value (0.1) instead of the user-specified value was being used after unserialization. This affects both real-time scoring and native scoring when you use the sp_rxPredict and PREDICT functions.
This issue is fixed in the following cumulative update for SQL Server:
Each new cumulative update for SQL Server contains all the hotfixes and all the security fixes that were included with the previous cumulative update. Check out the latest cumulative updates for SQL Server:
Microsoft has confirmed that this is a problem in the Microsoft products that are listed in the "Applies to" section.
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