code: def _assemble_bin_class_output(self, estimator_params):
      # Base score is calculated based on
      # https://github.com/dmlc/xgboost/blob/8de7f1928e4815843fbf8773a5ac7ecbc37b2e15/src/objective/regression_loss.h#L91
      # return -logf(1.0f / base_score - 1.0f);
      base_score = 0.0
      if self._base_score != 0.0:
          base_score = -math.log(1.0 / self._base_score - 1.0)
  
      expr = self._assemble_single_output(
          estimator_params, base_score=base_score
      )
  
      proba_expr = self._bin_class_convert_output(expr)
  
      return ast.VectorVal(
          [
              ast.BinNumExpr(
                  ast.NumVal(1.0), proba_expr, ast.BinNumOpType.SUB
              ),
              proba_expr,
          ]
      )
  
imports: import json
  import math
  import numpy
  from m2cgen import ast
  from m2cgen.assemblers import utils
  from m2cgen.assemblers.base import ModelAssembler
  from m2cgen.assemblers.linear import _linear_to_ast
label_desc: Use image node_id 5 for calling the BaseBoostingAssembler obj's underlying member method code with example usage: obj._assemble_bin_class_output(estimator_params) and returns: ast