Open velezbeltran opened 1 year ago
It seems that LGBMRegressor already supports quantile regression. I haven't checked other libraries yet. In LGBMRegressor, we need to add alpha
, objective="quantile"
. To pass these parameters to LGBMRegressor in flaml, the simplest way is to use the "custom_hp" argument in AutoML.fit()
. See https://microsoft.github.io/FLAML/docs/Use-Cases/Task-Oriented-AutoML/#a-shortcut-to-override-the-search-space for an example.
Thanks @sonichi will try it out.
Hello!
I was wondering if there is any native way of doing quantile regression with Flaml or any quick way of going about setting it up so that it works with it. I was taking a look at the tutorials and it wasn't clear to me how to do so.
Alternatively, if there isn't one, happy to make a PR implementing it if people support this feature.
Thank you!