class_docstr: Compute effect of treatment using a generalized linear model such as logistic regression.
  
  Implementation uses statsmodels.api.GLM.
  Needs an additional parameter, "glm_family" to be specified in method_params. The value of this parameter can be any valid statsmodels.api families object. For example, to use logistic regression, specify "glm_family" as statsmodels.api.families.Binomial().
code: def _build_model(self, data: pd.DataFrame):
      features = self._build_features(data)
      model = sm.GLM(
          data[self._target_estimand.outcome_variable],
          features,
          family=self.family,
      ).fit()
      return (features, model)
  
file_path: dowhy/dowhy/causal_estimators/generalized_linear_model_estimator.py
imports: import itertools
  from typing import Any, List, Optional, Union
  import pandas
  import statsmodels.api
  from dowhy.causal_estimator import CausalEstimator
  from dowhy.causal_estimators.regression_estimator import RegressionEstimator
  from dowhy.causal_identifier import IdentifiedEstimand
label_desc: Use image node_id 3 for calling the GeneralizedLinearModelEstimator obj's underlying member method code with example usage: obj._build_model(data) and returns: features,  model