a <number> sets the momentum parameter, alpha a <options> the algorithm command ac <weight;> add connection ah <layer> add hidden unit b <options> benchmarking c clear the network cd <directory> changes the working directory to <directory> ci <real> clear and initialize the network ct <filename> makes a copy to <filename> d <options> set delta-bar-delta parameters e <number(s)> set the learning rate eta f <options> lots of formatting options i <filename> read input from the file k <reals> kick the network l <layer> list the values of units on that layer m <numbers> make a network onu <unit> turn on a unit ofu <unit> turn off a unit onw <weight> turn on a weight ofw <weight> turn off a weight p <options> list information about training patterns pr <options> the predict command pw <real> prune weights q quit qp <options> set quickprop parameters r <options> run the training algorithm rp <options> rprop parameters rt <options> read the training set patterns rw <filename> read the weights rx <filename> read the extra training set patterns s <seed> seed value se <filename> save almost everything si <option> increment seed ss <options> supersab command sw <filename> save weights swe <int> save weights every so often swem <option> save weights every test set minimum t <options> list testing file statistics of various sorts t <real> tolerance per output unit, between 0 and 1 tf <filename> gives the file name with testing patterns to <real> tolerance overall tpu <real> tolerance per output unit, any value tr <int> special test for a recurrent network trp <int> special test for a recurrent network u <option> recurrent classification training set data v <option> recurrent classification test set data w <layer> <unit> list weights leading into unit