# Classifying time series data that overlap

I am working with Time-Series Data that has to be classified into two classes (Blue and Red) or at least Classify the data as one class (Red), I'm unable to come up with features that distinctly separate the data.

Please advise as to how do I need to approach this problem.

You could calculate the distance between time series using Dynamic Time Wrapping DTW and then you could cluster them using K-means or so. Here is a python implementation of the DTW or use the dtw package in R.