Model for classifying time-series data with distinct features?
This specific problem looks at the pattern across the whole data I.e. pattern will not show up from time &lt; -3 or time > 3 for a given curvature. 

You can try two models :


Simple feed-forward Network with number of inputs = number of time steps (Maybe scale / shift the data so that it always has the same number of time steps )


This should be able to detect some patterns for classification (Like f(0) must be less that f(4))


Univariate LSTM with different sizes of time steps in each sample 


This should be able to learn that f(x) should stay near constant, reduce and then increase and return to constant

Both networks will have a sigmoid in output layer since it is a binary classification problem. 

Code exmaple for LSTM : https://machinelearningmastery.com/sequence-classification-lstm-recurrent-neural-networks-python-keras/