I am trying to build a machine learning model which predicts a single number from a sequence of numbers.
Please fell free to have a look at this minimal example in Google Colab to understand what I am talking about.
You can imagine my dataset to look something like this:
|Index||x data||y data|
In a nutshell, my goal is the following: Predicting a single number from a sequence of numbers.
- np.array([3.461, 3.478, 3.478, 3.485, 3.489, 3.489, 3.492]) => 3.281
- np.array([3.469, 3.481, 3.481, 3.495, 3.495]) => 3.271
Additionally it is important to understand, that the lengths of my input sequences may vary and are not of the same shape.
I was able to train my model (as you can see in the minimal example) but apparently the desired output is nothing at all like the one I expected it to be. Right now I’m stuck with this problem. I was expecting it to be working just fine, because I saw the loss decreasing.
Apparently this is not the case. I would be very thankful if you could find the time to have a look at the minimal example I provided.
Thanks in advance!