Train

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6. def apply [Summary] (iteration: () ⇒ Summary, maxIterations: Option[Int], output: Option[File], saveState: Option[(File) ⇒ Unit], loadState: Option[(File) ⇒ Unit], description: Option[String], outputIterations: Option[Int], convergence: Option[(List[(Int, Summary)]) ⇒ Boolean], maxHistory: Option[Int], log: (String) ⇒ Unit)(implicit arg0: ReadWritable[Summary]): Unit

   Resumable model training with a status summary.

   Resumable model training with a status summary.

   iteration

   One iteration of learning, returning some summary of the computation

   maxIterations

   Hard maximum number of iterations of learning.

   output

   Target for saving the final model (and periodic intermediate models if outputIterations is defined).

   saveState

   Saves the state of the model to the given folder. Mandatory if output is not None.

   loadState

   Loads the state of the model from the given folder. Mandatory if output is not None.

   description

   Some (human-readable) description of the source of the model and data. For checking if the right model is stored on disk for resumed training.

   outputIterations

   If defined, saves the intermediate state of the model (and its history) every outputIterations iterations (e.g. every 50 iterations if outputIterations=Some(50)).

   convergence

   Test if the model has converged from a list of iteration numbers and summaries. The length of the list is maxHistory if maxHistory is defined, else the length of the history list is unbounded.

   maxHistory

   Maximum length of history provided to convergence.

   log

   Where status messages go.

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