Performance of Info-theoretic extraction

[maffei2443]

Hello.
I've been using PyMFE to extract metafeatures(MtF) when faced an unexpected (to me at least) execution time.
Specifically, the time spent for extracting all information theoretic was quite large, exceeding by far the total amount
of all the other groups.
The extraction process I performed was simple: to extract MtF from each group separately using a sliding windows w = 300 with step of 10. This process was repeated 2500 for each MtF group. The total execution time is show on the table below:

Duration	Group
34.5s	concept
24.1s	itemset
6.1min	complexity
34.1s	clustering
3.5min	relative
42.4min	info-theory
15.9s	model-based
43.3s	statistical
3.5min	landmarking

The database used was elec2.
I would like to know possible causes of such huge difference on extraction time or whether this is the expected behavior.
NOTE: each time involver other computations such as model training and evaluation. However, the code is the same for all experiments, the only difference being the MtF group employed for characterizing the windows.