(Backpropagation only): The coefficient to multiply the computed weight gradient by. The recommended value is about 0.1. The parameter can be set via param1 of the constructor.

(Backpropagation only): The coefficient to multiply the difference between weights on the 2 previous iterations. This parameter provides some inertia to smooth the random fluctuations of the weights. It can vary from 0 (the feature is disabled) to 1 and beyond. The value 0.1 or so is good enough. The parameter can be set via param2 of the constructor.

(RPROP only): Initial magnitude of the weight delta. The default value is 0.1. This parameter can be set via param1 of the constructor.

(RPROP only): The maximum value of the weight delta. It must be >1, the default value is 50. The parameter can only be changed explicitly by modifying the structure member.

(RPROP only): The minimum value of the weight delta. It must be >0, the default value is FLT_EPSILON. The parameter can be set via param2 of the constructor.

(RPROP only): The decrease factor for the weight delta. It must be <1, default value is 0.5 that should work well in most cases, according to the algorithm's author. The parameter can only be changed explicitly by modifying the structure member.

(RPROP only): The increase factor for the weight delta. It must be >1, default value is 1.2 that should work well in most cases, according to the algorithm's author. The parameter can only be changed explicitly by modifying the structure member.

The termination criteria for the training algorithm. It identifies how many iterations is done by the algorithm (for sequential backpropagation algorithm the number is multiplied by the size of the training set) and how much the weights could change between the iterations to make the algorithm continue.

The training algorithm to use