parameters: (self, x, y)
return_statement: return self.fit(x, y)
docstring: Incremental fit on a batch of samples.
  
      This method is expected to be called several times consecutively
      on different or the same chunks of the dataset. This either can
      implement iterative training or out-of-core/online training.
      This is especially useful when the whole dataset is too big to
      fit in memory at the same time. Or when model is taking long time
      to converge, and you want to split up training into subparts.
  
      Args:
        x: matrix or tensor of shape [n_samples, n_features...]. Can be
        iterator that returns arrays of features. The training input
        samples for fitting the model.
        y: vector or matrix [n_samples] or [n_samples, n_outputs]. Can be
        iterator that returns array of targets. The training target values
        (class label in classification, real numbers in regression).
  
      Returns:
        Returns self.
docstring_summary: Incremental fit on a batch of samples.
docstring_tokens: Incremental fit on a batch of samples .
function: def partial_fit(self, x, y):
      """Incremental fit on a batch of samples.
  
      This method is expected to be called several times consecutively
      on different or the same chunks of the dataset. This either can
      implement iterative training or out-of-core/online training.
      This is especially useful when the whole dataset is too big to
      fit in memory at the same time. Or when model is taking long time
      to converge, and you want to split up training into subparts.
  
      Args:
        x: matrix or tensor of shape [n_samples, n_features...]. Can be
        iterator that returns arrays of features. The training input
        samples for fitting the model.
        y: vector or matrix [n_samples] or [n_samples, n_outputs]. Can be
        iterator that returns array of targets. The training target values
        (class label in classification, real numbers in regression).
  
      Returns:
        Returns self.
      """
      return self.fit(x, y)
function_tokens: def partial_fit ( self , x , y ) : return self . fit ( x , y )