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)))

This is a follow-up for mlpack/mlpack#2647. Based on the experiments in mlpack/mlpack#2777 we figured it makes sense to remove the boost::variant approach. This should not only make it easier for new-comers to contribute to the network codebase (the boost::variant and visitor approach can be confusing) but also reduce the memory usage during the bu

• What's wrong?

Rank widget does not show that Manual selection is active, if:

1. Best ranked was active.
2. I clicked into the white part of the table to deselect.

The "Select Attributes" radio button still has "Best ranked" active, but nothing is selected (and the status bar shows that nothing gets to the output). Instead, the "Select Attributes" radio button should switch to "

The built-in Screen logger is fantastic for outputting log messages to the console but what if the user wants to output them to a file instead? Yes, they can use MonoLog but that requires typing stuff into composer and waiting. I think we can provide alot of value by way of user experience by incl

The PR JuliaData/CategoricalArrays.jl#310 means that an array with elements of type Symbol can no longer be wrapped as a CategoricalArray.

This means all MLJ documentation and test code that uses symbols in categorical data must be refactored to use strings instead.

These repos, at least, need checking/refactoring, in order of priority:

• MLJ

• [x]

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