parameters: (self, margin)
docstring: Set base margin of booster to start from.
  
          This can be used to specify a prediction value of existing model to be
          base_margin However, remember margin is needed, instead of transformed
          prediction e.g. for logistic regression: need to put in value before
          logistic transformation see also example/demo.py
  
          Parameters
          ----------
          margin: array like
              Prediction margin of each datapoint
docstring_summary: Set base margin of booster to start from.
docstring_tokens: Set base margin of booster to start from .
function: def set_base_margin(self, margin) -> None:
          """Set base margin of booster to start from.
  
          This can be used to specify a prediction value of existing model to be
          base_margin However, remember margin is needed, instead of transformed
          prediction e.g. for logistic regression: need to put in value before
          logistic transformation see also example/demo.py
  
          Parameters
          ----------
          margin: array like
              Prediction margin of each datapoint
  
          """
          from .data import dispatch_meta_backend
          dispatch_meta_backend(self, margin, 'base_margin', 'float')
function_tokens: def set_base_margin ( self , margin ) -> None : from . data import dispatch_meta_backend dispatch_meta_backend ( self , margin , 'base_margin' , 'float' )