pyFM
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coreylynch
Factorization machines in python
Since the computation of the model is time-consuming, is there any way to save the model for later prediction?
how to do unbalansed data classification, may you add weights as input parameter for example this has https://github.com/dstein64/PyFactorizationMachines
hello ,dose anyone find that the examply pyFM contains and showed in README is overfit? the mse in TrainData and TestData is 0.4 and 0.8......that is overfit,so dose the example...
Hi, From the code I see: # Regularization Parameters (start with no regularization) self.reg_0 = 0.0 self.reg_w = 0.0 self.reg_v = np.repeat(0.0, num_factors) However, I don't see where the regularization...
I add an argument to activate regularization. The regularization have been defined, but there is no the argument of class FM. Thank you, your great lib.
Permits having the same result when running the same experiment twice. Follows recommendation given at https://github.com/coreylynch/pyFM/issues/19
Use https://cython.readthedocs.io/en/latest/src/userguide/numpy_tutorial.html#efficient-indexing-with-memoryviews instead of casting the arrays.data attribute into a DOUBLE*. The former strategy generated segfaults in some servers.
pylibfm is out of the game. It is slow, it crashes on large datasets, sometimes simply diverge and hardly can compete in quality. https://arogozhnikov.github.io/2016/02/15/TestingLibFM.html
I tried pip but i got this: LINK : fatal error LNK1181: cannot open input file 'm.lib' error: command 'C:\\Program Files (x86)\\Microsoft Visual Studio 14.0\\VC\\BIN\\x86_amd64\\link.exe' failed with exit status 1181
