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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _set_param_recursive(self, pipeline_steps, parameter, value):
 """Recursively iterate through all objects in the pipeline and set a given parameter. Parameters pipeline_steps: array-like List of (str, obj) tuples from a scikit-learn pipeline or related object parameter: str The parameter to assign a value for in each pipeline object value: any The value to assign the parameter to in each pipeline object Returns ------- None """

        for (_, obj) in pipeline_steps:
            recursive_attrs = ['steps', 'transformer_list', 'estimators']
            for attr in recursive_attrs:
                if hasattr(obj, attr):
                    self._set_param_recursive(getattr(obj, attr), parameter, value)
            if hasattr(obj, 'estimator'):  # nested estimator
                est = getattr(obj, 'estimator')
                if hasattr(est, parameter):
                    setattr(est, parameter, value)
            if hasattr(obj, parameter):
                setattr(obj, parameter, value)