I have a simple regression task (using a LightGBMRegressor) where I want to penalize negative predictions more than positive ones. Is there a way to achieve this with the default regression LightGBM objectives (see https://lightgbm.readthedocs.io/en/latest/Parameters.html)? If not, is it somehow possible to define (many example for default LightGBM model) and pass a custom regression objective?

Describe the bug
When the finalizer is called for CLR JvmObjectId objects, it calls the rm DotnetBackend method and this calls goes through the JvmBridge class. Because the rm call goes through [JvmBridge.CallJavaMethod](https://github.com/do

Description

It would be nice to provide API which allows to specify the Azure credentials in the code. Currently the Azure storage implementation only relies on the environment variables, which makes it difficult to access two independent storages in the same program. In case of AWS S3 the problem does not exists because the API allows to use a custom rusoto S3 client with a static credentials