harish@mist.CS.ORST.EDU (Harish Pillay) (04/26/89)
I am taking a grad course on NN and am planning on doing a project trying to predict foreign exchange rates specifically the following: US$ vs British Pound vs Japanese Yen vs Singapore $ vs German Marks I am using NeuralWorks and am thinking of using the backprop strategy. So far, all I've done is to gather the exchange rates reported in the WSJ from March 17 to today. I've normalized it to be within 0 and 1 but my problem is in trying to train the network. Has anyone out there done anything similar to this? If so, what desired output values did you use to train? I understand that it is naive to just take the rates themselves and try to get a pattern or correlation. Should I be looking at other values too? What kind of transfer function should I use? I think one hidden layer may be sufficient. I would really appreciate any suggestions, and will post something once I get this project done. Thanks. ---------------------------------------------------------------------------- Harish Pillay Internet: harish@ece.orst.edu Electrical and Computer Engineering MaBell: 503-758-1389 (home) Oregon State University 503-754-2554 (office) Corvallis, OR 97331 ----------------------------------------------------------------------------
andrew@berlioz (Andrew Palfreyman) (04/26/89)
In article <10198@orstcs.CS.ORST.EDU>, harish@mist.CS.ORST.EDU (Harish Pillay) writes: > I am taking a grad course on NN and am planning on doing a project trying to > predict foreign exchange rates specifically the following: > US$ vs British Pound vs Japanese Yen vs Singapore $ vs German Marks > I am using NeuralWorks and am thinking of using the backprop strategy. > ...but my problem is in trying to train the network. Has anyone out there > done anything similar to this? If so, what desired output values did > you use to train? I understand that it is naive to just take the rates > themselves and try to get a pattern or correlation. Should I be looking > at other values too? What kind of transfer function should I use? I think > one hidden layer may be sufficient. One brute force method, to separate the chicken from the egg, might be to use the changes instead of the absolute values (especially since you're using localised data which doesn't span a boom or a crash). Maybe then you could use 3 inputs in parallel (3 currencies) and 2 outputs, and just ring the changes (5c3 = 10 ways) until the input deltas produce correct output deltas. An associative net might do this better. Else, you could play with recursive nets (Jordan, etc.), whereby you try and predict tomorrow's 5-vector, given today's. -- Andrew Palfreyman USENET: ...{this biomass}!nsc!logic!andrew National Semiconductor M/S D3969, 2900 Semiconductor Dr., PO Box 58090, Santa Clara, CA 95052-8090 ; 408-721-4788 there's many a slip 'twixt cup and lip