I am confusing about the relationship between MI score and correlation score. I've searched for some information and know that:
with Cov(𝑋,𝑌) we look at what non-independence does to their product, while in 𝐼(𝑋,𝑌) we look at what non-independence does to their joint probability distribution.
(Mutual information versus correlation)
But when I plot the graph of MI score and correlation score, I am still confused. In the below graph, I am using the rolling window to continue plot the score between 'Topic' and 'Emotion' As you can see in the x-axis where the range between 140-160, the correlation(Pearson) score is quite low, whereas the same period in the MI graph, the score is no significant low or high