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Yeah I understand the problem. I'm just a newbie still figuring out a way to rectify this issue.
I thought of crude way to fix this by varying the input value to match the output value from the trained model. So after some experiments I found out that if the test values(input values) are in the close range of output value, then they share some similar properties. So, maybe, if we provide a range, in which a certain input value coincides with the output value , we would be getting the approximate prediction.
You seem to be using the test target values as inputs to the model - surely not a good idea.
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