Feed-forward neural network solution for python
Project description
Basic usage of the package:
>>> from ffnet import ffnet, mlgraph, savenet, loadnet, exportnet >>> conec = mlgraph( (2,2,1) ) >>> net = ffnet(conec) >>> input = [ [0.,0.], [0.,1.], [1.,0.], [1.,1.] ] >>> target = [ [1.], [0.], [0.], [1.] ] >>> net.train_tnc(input, target, maxfun = 1000) >>> net.test(input, target, iprint = 2) >>> savenet(net, "xor.net") >>> exportnet(net, "xor.f") >>> net = loadnet("xor.net") >>> answer = net( [ 0., 0. ] ) >>> partial_derivatives = net.derivative( [ 0., 0. ] )
For instalation instructions and documentation go to http://ffnet.sourceforge.net.
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Filename, size & hash SHA256 hash help | File type | Python version | Upload date |
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ffnet-0.8.4-py2.7-linux-x86_64.egg (348.6 kB) Copy SHA256 hash SHA256 | Egg | 2.7 | |
ffnet-0.8.4-py2.7-win-amd64.egg (311.1 kB) Copy SHA256 hash SHA256 | Egg | 2.7 | |
ffnet-0.8.4-py3.5-linux-x86_64.egg (359.9 kB) Copy SHA256 hash SHA256 | Egg | 3.5 | |
ffnet-0.8.4-py3.6-linux-x86_64.egg (360.7 kB) Copy SHA256 hash SHA256 | Egg | 3.6 | |
ffnet-0.8.4-py3.7-linux-x86_64.egg (355.0 kB) Copy SHA256 hash SHA256 | Egg | 3.7 | |
ffnet-0.8.4.tar.gz (55.8 kB) Copy SHA256 hash SHA256 | Source | None |