Model Predicted results vary if data is fed from sql trasnformation block

2021-08-17T10:31:32.65+00:00

Hi,
I created a model to read training and testing data from 2 respective cosmos db tables and used an sql transformation block to rename the column names and used it for training and in score model as shown in snapshot (modela.jpg) . The Predicted parameter (scored label) is very much different and incorrect (refer onlysqltrans.jpg)
When I use a "convert to csv" block connected to output of sql transformation block (refer modelb.jpg for model diagram ) and then use it in training , I get expected results ( refer withcsvblock.jpg) .
The Mean Absolute error in first case was 51.2 while in modelb was only 0.09

I used a convert to dataset block after sql transform block and used that to connect to training model
but that too gave the same result as modela output

In case you want to see what sql transformation i used
123904-modelb.jpg123936-withcsvblock.jpg123945-modela.jpg123992-onlysqltrans.jpg

  select  "['CombiTimeTable.y[1]']" as av1 ,"['CombiTimeTable.y[2]']" as av2,"['CombiTimeTable.y[3]']" as av3,"['CombiTimeTable.y[4]']" as av4,"['CombiTimeTable.y[5]']" as av5,"['CombiTimeTable.y[6]']" as av6,"['CombiTimeTable.y[7]']" as av7,"['CombiTimeTable.y[8]']" as av8,"['CombiTimeTable.y[9]']"  as av9 from t1  

Thanks

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  1. YutongTie-MSFT 53,966 Reputation points Moderator
    2021-09-02T15:40:14.457+00:00

    @HCL-AZURE-Cloud-Connected-ECOSystems

    Update for this thread, this issue has been forwarded to product team, I will let you know any news I get from them back. Thanks for the feedback again.

    Regards,
    Yutong

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