Imaginary_Carrot4092
Imaginary_Carrot4092 OP t1_iqvqztc wrote
Reply to comment by PassionatePossum in [D] Model not learning data by Imaginary_Carrot4092
Yes your assumption 1 is exactly right. The network I am using is very simple with 2 hidden layers (I am not sure if this model is enough to learn this data). This is not a time series data.
The input is the number of hours it takes for a certain process to complete and the output is one of the process variables.
Imaginary_Carrot4092 OP t1_iqvj2lq wrote
Reply to comment by ThrowThisShitAway10 in [D] Model not learning data by Imaginary_Carrot4092
I am using MSE. But the data points in the images are not predictions. They are the training data.
Imaginary_Carrot4092 OP t1_iqv9whz wrote
Reply to comment by dumpyact in [D] Model not learning data by Imaginary_Carrot4092
Do you mean to reduce the LR as training progresses ? But I already tried playing with the LR. It doesn't seem to change anything. Yes, the losses have a different magnitude but the pattern is the same.
Imaginary_Carrot4092 OP t1_iqv9s87 wrote
Reply to comment by PassionatePossum in [D] Model not learning data by Imaginary_Carrot4092
Ok..I have added a few images to clarify this. Firstly, how can I make sure that I can learn something out of my data based on its distribution.
Submitted by Imaginary_Carrot4092 t3_xudng9 in MachineLearning
Imaginary_Carrot4092 OP t1_iqvrbcz wrote
Reply to comment by sanderbaduk in [D] Model not learning data by Imaginary_Carrot4092
Ok. Thanks