In the linked article a border pairs method is described which have numerous advantages against the backpropagation algorithm.
Does anyone observed any deficiency?
Article Border Pairs Method—constructive MLP learning classification algorithm
I have never used SVM but i have used backpropagation method (modified with momentum term added, adaptive learning rate, with trainbr, trainrp and trainscg functions) for various purposes. I found that its very much suitable for training complex real-valued and noisy kind of data.
What do you think about Border Pairs Method (see the linked article)
Article Border Pairs Method—constructive MLP learning classification algorithm
presently busy with something, will see and respond ! thanks for sharing high impact paper !
Q: I noticed that you present results on noisy patterns starting from 0% noise. Is that a problem for your method?
A: On the contrary, BPM results are better than those in the backpropagation method. BPM method is even able to effectively eliminate the noise.
Q: If you have noisy patterns throughout (always 10% noise) will that degrade the performance, or, if the noise diminishes, which I could imagine would be a problem for any constructive algorithm?
A: Yes, noise degrade the results, but less than by the backpropagation method. Noise can be also reduced without any special problems for algorithm.
I try to contact you by telephone , email and Skype but where you are ?
I receive your paper of 14 June and I ask if this paper is for a pubblication or is the first chapter of the book ? Please contact me.
Germano resconi
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