docstr: Get xgboost specific parameters.
docstr_tok: ["Get","xgboost","specific","parameters","."]
code: def get_xgb_params(self):
      """Get xgboost specific parameters."""
      params = self.get_params()
  
      # Parameters that should not go into native learner.
      wrapper_specific = {
          "importance_type",
          "kwargs",
          "missing",
          "n_estimators",
          "use_label_encoder",
          "enable_categorical",
          "early_stopping_rounds",
          "callbacks",
          "feature_types",
      }
      filtered = {}
      for k, v in params.items():
          if k not in wrapper_specific and not callable(v):
              filtered[k] = v
  
      return filtered
  
file_path: ivy/ivy/functional/frontends/xgboost/sklearn.py
imports: import ivy
  from ivy.functional.frontends.sklearn.base import BaseEstimator
  from ivy.functional.frontends.sklearn.base import ClassifierMixin
  from .training import train
  from .core import Booster
label_desc: Use image node_id 5 for calling the XGBModel obj's underlying member method code with example usage: obj.get_xgb_params() and returns: filtered