parameters: (self, y, raw_predictions, **kargs)
return_statement: return y - expit(raw_predictions.ravel())
docstring: Compute the residual (= negative gradient).
  
          Parameters
          ----------
          y : 1d array, shape (n_samples,)
              True labels.
  
          raw_predictions : 2d array, shape (n_samples, K)
              The raw_predictions (i.e. values from the tree leaves) of the
              tree ensemble at iteration ``i - 1``.
docstring_summary: Compute the residual (= negative gradient).
docstring_tokens: Compute the residual ( = negative gradient ) .
function: def negative_gradient(self, y, raw_predictions, **kargs):
          """Compute the residual (= negative gradient).
  
          Parameters
          ----------
          y : 1d array, shape (n_samples,)
              True labels.
  
          raw_predictions : 2d array, shape (n_samples, K)
              The raw_predictions (i.e. values from the tree leaves) of the
              tree ensemble at iteration ``i - 1``.
          """
          return y - expit(raw_predictions.ravel())
function_tokens: def negative_gradient ( self , y , raw_predictions , * * kargs ) : return y - expit ( raw_predictions . ravel ( ) )