Rafey Iqbal Rahman
Rafey Iqbal Rahman
> I guess you can just pickle the final pipeline object (tpot.fitted_pipeline_), which is a normal sklearn pipeline and can be used independently from tpot. I tried but doing that...
> Where did you get the error? I tried it and it worked. Can you show the code that works?
Thanks for the code. It worked. But when I loaded the model on Flask, I'm getting a strange error. `ValueError: matmul: Input operand 1 has a mismatch in its core...
I called the pipeline using pickle.load. The shape of the data is 18x3. The datatype is float. The link is accessible now. I'll try pipeline.predict to make predictions.
You are right. Actually, I was checking what is the reason for the error. Turns out that when I did .predict(y), I got the same error as I mentioned above....
Can you show a practical example of reshaping the data? Or can you please do the same in the notebook's link so I can get an idea?
This doesn't work. Also, I'm getting an error message saying that the features should be 2D while the target should be 1D.
When converted into 2D, this is what I got. 
Also, as seen [here](https://stackoverflow.com/questions/55309176/how-to-correct-numpy-and-tpot-array-shapes-error), TPOT lacks multi-label regression ability.
No, I have a single variable at the output. The shape of X is (18, 2) and that of y is (18, 1).