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

When grouping by variable in Pivot Table, it would be nice if Group By would output an actual date for datetime variables.

E.g.:

• A mean of [2020-01-01, 2020-01-02, 2020-01-03] would output 2020-01-02.
• A median of [2020-01-01, 2020-01-02, 2020-01-03, 2020-01-03, 2020-01-04] would output 2020-01-03.
• A sum ... Don't know. Probably output a float?
• Min, max ... This one is obvious.
• Va

String representations of dataset objects are used for previewing their contents from the terminal. When converting a Dataset object to a string, we build a table using ascii characters. The current table has fixed width columns that do not take full advantage of the terminal real estate if the dataset only contains a few columns.

echo $dataset;

<img width="574" alt="Annotation

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