Batch Gradient Descent

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Revision as of 18:28, 15 April 2024 by Rice (talk | contribs)

In batch gradient descent, the unit of data is the entire dataset, in contrast to Stochastic Gradient Descent whose unit of data is one data point. It uses the average of the computed gradients to update the weights of a batch of data points.

  • Faster
  • Less performing/precise (not always)

A variation is to use smaller batches (not the entire dataset). It mitigates the lack in precision.