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The values of parameters are derived via learning. Examples of hyperparameters include learning rate, the number of hidden layers and batch size. [citation needed] The values of some hyperparameters can be dependent on those of other hyperparameters. For example, the size of some layers can depend on the overall number of layers.
A touch screen displays choices to the voter, who selects choices, and can change their mind as often as needed, before casting the vote. Staff initialize each voter once on the machine, to avoid repeat voting. Voting data and ballot images are recorded in memory components, and can be copied out at the end of the election.