Option for groupKFold for regression problems about flaml

[sonichi]

Hi @suryajayaraman there are two ways to go about it:

1. Add support for split_type='group' in AutoML.fit(), in addition to 'stratified' and 'uniform'. Group weights can be passed and handled in a similar way as 'sample_weight'. Feel free to create a PR.
2. Use flaml.tune.run() to which you can pass a custom function evaluate_config. You can put the groupKFold cross-validation inside that custom function.

[dtquandt]

+1, I'm having the same issue but for classification. Trying to understand the underlying code better so that I can think about whether I feel confident adding it myself.

[sonichi]

@dtquandt @suryajayaraman Let's discuss on gitter about it.

[sonichi]

@suryajayaraman @dtquandt The PR is created. Please let us know your suggestions.