Mercurial > pylearn
view noise.py @ 501:4fb6f7320518
N-class logistic regression top-layer works
author | Joseph Turian <turian@gmail.com> |
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date | Tue, 28 Oct 2008 13:54:01 -0400 |
parents | 643dbccde1fc |
children |
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def binomial(input, rstate, p = 0.75): """ Op to corrupt an input with binomial noise. Generate a noise vector of 1's and 0's (1 with probability p). We multiply this by the input. @note: See U{ssh://projects@lgcm.iro.umontreal.ca/repos/denoising_aa} to see how rstate is used. """ noise = rstate.gen_like(('binomial',{'p': p, 'n': 1}), input) noise.name = 'noise' return noise * input