By J.L. Peterson
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Additional info for Computer Programs for Spelling Correction: An Experiment in Program Design
Where backpropagation ami RPROP differ is in the way in which the gradients are used. In a simple XOR example, it typically takes backpropagation over 500 iterations to converge to a solution with an error rate o f below one percent. It will usually take RPROP around 30 to 100 iterations to accomplish the same thing. This large increase in performance is * reason why RPROP is a very popular training algorithm. o ik Another factor in the popularity o f RPROP is that there are no necessary training parameters to the RPROP algorithm.
The gradients will have changed, because the underlying weights changed. We w ill use these new gradient values to calculate a new value o f c for each weight. 01641086135590903 = 1 1 From this we can determine each o f the weight change values. The value ol c is one in all cases. This means that none o f the gradients' signs changed. Because of this, the weight change value is the negative o f the weight update value. 01 for every weight. 12249838002549909 Everything continues to move in the same direction as in the first iteration.
T ra in in g Ite ra tio n #8 We begin the eight iteration by again calculating the gradients o f eaeh o f the weights. The weights have changed over the iterations that we skipped. This will cause the gradients to change. We will use the previous gradients along with these new gradients to calculate a new value o f c for each weight. 009100949661316388 = 1 H2 - > 0 1 : - 0 . 0 2 3 2 6 6 0 1 7 8 6 6 3 0 6 7 1 4 * - 0 . 0187 9 3 9 4 4 2 9 3 4 6 6 4 8 = 1 7 . 9 6 7 3 6 7 7 7 1 9 3 0 8 3 5E-4 * - 0 .