The BP algorithm, eq. (), is selected by setting MSTJN(5) = 0 (default). Its main parameters are the learning rate PARJN(1) ( in eq. ()), the momentum PARJN(2) ( in eq. ()), and the number of patterns per update MSTJN(2). We strongly advocate the use of an on-line updating procedure where MSTJN(2) is small. Routinely we use ten patterns per update for most applications -- occasionally an order of magnitude more. The learning rate is the parameter that requires most attention. Typical initial values are in the range and it is usually profitable to scale the learning rate in inverse proportion to the fan-in of the units so that different learning rates are used for different weight layers. The momentum should be in the range [0,1]. For HEP problems momentum values above 0.5 are seldom required. For parity problems and such, a momentum value close to unity is needed.
In contrast to earlier versions, JETNET 3.0 uses a normalized error to make the gradient, and hence the learning parameters are independent of the number of patterns used per update.