deepNN: updateStopping.classification – R documentation

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updateStopping.classification

updateStopping.classification function

A function to update the stopping criteria for a classification problem.

## S3 method for class 'classification'
updateStopping(
  dat,
  parms,
  net,
  truth,
  testoutput,
  count,
  monitor,
  mx,
  curcost,
  ...
)

`dat`	data object
`parms`	model parameters
`net`	an object of class network
`truth`	the truth, to be compared with network outputs
`testoutput`	a vector, the history of the stopping criteria
`count`	iteration number
`monitor`	logical, whether to produce a diagnostic plot
`mx`	a number to be monitored e.g. the cost of the best performing paramerer configuration to date
`curcost`	current measure of cost, can be different to the value of the loss function e.g. may consider smoothed cost (i.e. loss) over the last k iterations
`...`	additional arguments

curcost, testoutput and mx, used for iterating the maximisation process

Deep Learning

v1.0

GPL-3

Authors

Benjamin Taylor [aut, cre]

Initial release