class_docstr: simple wrapper of lightgbm , using importance ranking to select top-k features.
  
  Parameters
  ----------
  fixlen : int
      K for top-K important features.
class_docstr_tok: ["simple","wrapper","of","lightgbm",",","using","importance","ranking","to","select","top-k","features",".","Parameters","--","--","--","--","--","fixlen",":","int","K","for","top-K","important","features","."]
code: def __init__(self, fixlen: int = 10, *args, **kwargs):
      super(GBDTFeatureSelector, self).__init__()
      self.__fixlen = fixlen
      self.__args = args
      self.__kwargs = kwargs
  
file_path: AutoGL/autogl/module/preprocessing/feature_engineering/_selectors/_gbdt.py
imports: import numpy
  import pandas
  import torch
  import typing
  import autogl
  from autogl.data.graph import GeneralStaticGraph
  from ..._data_preprocessor_registry import DataPreprocessorUniversalRegistry
  import lightgbm
  from sklearn.model_selection import train_test_split
  from ._basic import BaseFeatureSelector
label_desc: Use image node_id 1 to create a new GBDTFeatureSelector object from inherited base classes: BaseFeatureSelector with example: obj = GBDTFeatureSelector(fixlen)