Trying out a simple example using TuneSearchCV with LGBMClassifier and it fails on start.

Environment:

Python 3.8.3
tune-sklearn 0.3.0
ray 1.3.0
macos mojave 10.14.6

Code:

from ray.tune.sklearn import TuneSearchCV

from lightgbm import LGBMClassifier

lgmb_param_dists = dict(

                boosting_type=['gbdt','dart','rf'],
                num_leaves=(10,500),
 

The "Unit tests, linux, min dependencies" workflow currently runs a "shellcheck" job. The "Unit tests, linux, latest dependencies" and "Unit tests, windows" workflows do not.

If that check is not necessary, let's delete it. If it is necessary, let's add it in all the unit test workflows.

I think this came in when @gsheni recently merged the min deps CI.

We should add a description to each feature defined in smartcore in the Cargo.toml file, we could use as example the Cargo.toml file of the serde project.

We should add also the documentation for the "serde" feature that currently is not present in the Cargo.toml file.

Not sure if we can u

Is your feature request related to a problem? Please describe.
Feature is not directly related to a problem, but is rather an enhancement of existing functionality. As suggested by Julian King on the facet Slack channel, we could add Maximum Relevance Minimum Redundancy (MRMR) as a feature selection algorithm.

The algorithm is explained in the following papers:
https://arxiv.org/pdf/1

Describe the solution you'd expect
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