regression

Hi I would like to propose a better implementation for 'test_indices':

We can remove the unneeded np.array casting:

Cleaner/New:
test_indices = list(set(range(len(texts))) - set(train_indices))

Old:
test_indices = np.array(list(set(range(len(texts))) - set(train_indices)))

Describe the bug

• W-THU is not supported right now. It only works if user specifies seasonal_period in setup

To Reproduce

Expected behavior
Would have expected it to automatically infer the freq = 52 from there.

Hi,

There are still parts of boost library that are used inside mlpack, more specifically in here

1. mlpack/src/mlpack/core/tree/cosine_tree/cosine_tree.hpp. // boost::heap
2. mlpack/src/mlpack/core/data/load_arff.hpp. // boost::tokenizer

We would like to replace this one with the standard library if possible. If someone is interested in taking this issue feel free to do so.

Hi @JavierAntoran @stratisMarkou,

First of all, thanks for making all of this code available - it's been great to look through!

Im currently spending some time trying to work through the Weight Uncertainty in Neural Networks in order to implement Bayes-by-Backprop. I was struggling to understand the difference between your implementation of `Bayes-by-Bac