Add support for group in learning to rank in lightgbm

import optuna.integration.lightgbm as lgb

params = {
    'objective': 'lambdarank',
    'metric': 'lambdarank',  # alias to ndcg.
    'eval_at': 3,
    'boosting_type': 'gbdt',
    
}

lgb.train(params,X_train, y_train, group=query_train,
        eval_set=[(X_val, y_val)], eval_group=[query_val], 
        eval_at=[3, 5])

the above throws an error

---> 33     auto_booster = LightGBMTuner(*args, **kwargs)
     34     booster = auto_booster.run()
     35     return booster

TypeError: __init__() got an unexpected keyword argument 'group'

grouping allows for keeping queries together.

[toshihikoyanase]

@gauthamzz Let me close this issue. Please feel free to re-open it or create new PRs if you have further problems.

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