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 _fit(self, data):
      self._sel = gbdt_gen(data, self.fixlen, *self.args, **self.kwargs)
  
file_path: AutoGL/autogl/module/_feature/selectors/se_gbdt.py
imports: from ..None import register_feature
  import lightgbm
  from sklearn.model_selection import train_test_split
  import psutil
  from .base import BaseSelector
  import numpy
  import copy
  import pandas
label_desc: Use image node_id 2 for calling the SeGBDT obj's underlying member method code with example usage: obj._fit(data) without return types