def assemble_tree_expr(t):
assembler = TreeModelAssembler(t)
return utils.apply_bin_op(
ast.SubroutineExpr(assembler.assemble()),
ast.NumVal(coef),
ast.BinNumOpType.MUL)
def _final_transform(self, ast_to_transform):
if self.average_output:
coef = 1 / self.n_iter
return utils.apply_bin_op(ast_to_transform, ast.NumVal(coef),
ast.BinNumOpType.MUL)
else:
return super()._final_transform(ast_to_transform)
def assemble(self):
trees = self.model.estimators_
def assemble_tree_expr(t):
assembler = TreeModelAssembler(t)
return assembler.assemble()
assembled_trees = [assemble_tree_expr(t) for t in trees]
return utils.apply_bin_op(
utils.apply_op_to_expressions(ast.BinNumOpType.ADD,
*assembled_trees),
ast.NumVal(1 / self.model.n_estimators), ast.BinNumOpType.MUL)
def _assemble_single_output(self,
estimator_params,
base_score=0.0,
split_idx=0):
estimators_ast = self._assemble_estimators(estimator_params, split_idx)
tmp_ast = utils.apply_op_to_expressions(ast.BinNumOpType.ADD,
*estimators_ast)
if base_score != 0.0:
tmp_ast = utils.apply_bin_op(ast.NumVal(base_score), tmp_ast,
ast.BinNumOpType.ADD)
result_ast = self._final_transform(tmp_ast)
return result_ast
