fmin_bfgs() got an unexpected keyword argument 'lr', train func does not take lr as parameter

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What steps will reproduce the problem?
1.net = nl.net.newff([[-1.2499051235,7.7401906134]], [2, 15, 1], 
[nl.trans.TanSig(), nl.trans.TanSig(), nl.trans.PureLin()])
2.error = net.train(inputs, targets, epochs = 1000, show = 50, goal = 0.02, lr 
= 0.001)
3.

What is the expected output? What do you see instead?


What version of the product are you using? On what operating system?
Neurolab 0.3.4, Linux Mint

Please provide any additional information below.

I can't adjust learning rate with adding additional parameter lr = "some float".

Original issue reported on code.google.com by [e-mail] on 19 Sep 2014 at 10:27

[Google Code Exporter]

TrainBFGS use scipy.optimize.fmin_bfgs for optimization. This implementation 
have not learing rate paremeter 
see:
http://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.optimize.fmin_b
fgs.html

Original comment by [e-mail] on 21 Sep 2014 at 7:07

[Google Code Exporter]

Original comment by [e-mail] on 23 Sep 2014 at 4:20

• Changed state: Done