Time Series Analysis, Time Series Forecasting, Data Science, Noise Reduction, Signal Processing.
for i in range(len(phases)-1): mis.append(mutual_info_regression(phases[i].reshape(-1, 1), phases[i+1])[0]) return np.array(mis) Here we leverage the calculation from the sklearn library. Now, there is a lot of ways of using mutual information. In this post, we will look for a cutoff point.