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License: Apache License 2.0
Implementation of CFGAN CFGAN: A Generic Collaborative Filtering Framework based on Generative Adversarial Networks
License: Apache License 2.0
Hello, I ignore the GAN model and only keep the reconstruction loss. I find that the performance is the same as the CF-GAN. P@5: 0.4928 on MovieLen 100K.
why the loss of the discriminator is negative ?
大佬能给加个注释嘛~辛苦啦
How to train the Discriminator by realData_result.detach().numpy?
fakeData_result=D(fakeData_ZP,useInfo_batch)
realData_result=D(realData,useInfo_batch)
d_loss = -np.mean(np.log(realData_result.detach().numpy()+10e-5) +
np.log(1. - fakeData_result.detach().numpy()+10e-5)) + 0*regularization(fakeData_ZP,realData_zp)
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