class_docstr: LightGBM Model
class_docstr_tok: ["LightGBM","Model"]
code: def __init__(
      self,
      loss="mse",
      early_stopping_rounds=50,
      num_boost_round=1000,
      **kwargs,
  ):
      if loss not in {"mse", "binary"}:
          raise NotImplementedError
      self.params = {"objective": loss, "verbosity": -1}
      self.params.update(kwargs)
      self.early_stopping_rounds = early_stopping_rounds
      self.num_boost_round = num_boost_round
      self.model = None
  
file_path: qlib/qlib/contrib/model/gbdt.py
imports: import numpy
  import pandas
  import lightgbm
  from typing import List, Text, Tuple, Union
  from ...model.base import ModelFT
  from ...data.dataset import DatasetH
  from ...data.dataset.handler import DataHandlerLP
  from ...model.interpret.base import LightGBMFInt
  from ...data.dataset.weight import Reweighter
  from qlib.workflow import R
label_desc: Use image node_id 1 to create a new LGBModel object from inherited base classes: ModelFT, LightGBMFInt with example: obj = LGBModel(loss, early_stopping_rounds, num_boost_round)