This package is depracated. Use Logical Factorisation Machines instead.
Code is full compatible with Python 2 and 3. To install and test the packge run the following commands:
>>> git clone https://github.com/TammoR/OrMachine
>>> cd OrMachine/
>>> pip3 install .
>>> python3 tests/test_ormachine.py
This test should finish about one second or less.
If you like to compile the Cython coude yourself
>>> python3 setup.py build_ext --inplace
Multi-core support comes from OpenMP. For single core use, remove the corresponding flags in the setup.py.
See examples folder for jupyter notebooks.
import ormachine
import numpy as np
# generate toy data in {-1,1} domain
X = 2*np.array([[0,0,1,1,0,0],[1,1,0,0,0,0],[0,0,1,1,1,1]])-1
X = np.concatenate(200*[X])
# invoke machine object
orm = ormachine.machine()
data = orm.add_matrix(val=X, sampling_indicator=False)
# add layer
layer1 = orm.add_layer(size=3, child=data, lbda_init=2)
# run inference
orm.infer()
Should you experience lack of convergence (e.g. one factor matrix all 'off', the other uniform random), try initialising the larger factor matrix mostly to ones and the smaller factor matrix to zeros. E.g. by defining the hidden layer as follows:
hidden = orm.add_layer(size=size, child=data, lbda_init=1.6, z_init=.9, u_init=.1)
You may also try to fix lbda for hold lbda fixed for the first few iteration:
hidden = orm.add_layer(size=size, child=data, lbda_init=1.5, z_init=.9, u_init=.1)
orm.infer(burn_in_max=500, fix_lbda_iters=50)
Alternatively, centroids from a simple mixture model may provide a good initialisation.
If you get an error clang: error: : errrorunsupported option '-fopenmp',
point to gcc as your default compiler (possibly after
installing it using homebrew: brew instal lgcc), e.g. with
export CC=/usr/local/bin/g++-7
Currently OpenMP support is not working. A promising route to resolving this is to build your own clang compiler which supports OpenMP, described here.
Choose your compiler by setting the CC variable, here
export CC=/usr/local/myclang/build/bin/clang-5.0
This still throws an error that it can't find omp.h.
Setting C_INCLUDE_PATH to directories that include this file, e.g.
/usr/local/Cellar/gcc/7.1.0/lib/gcc/7/gcc/x86_64-apple-darwin16.5.0/7.1.0/include/usr/local/Cellar/llvm/4.0.0_1/lib/clang/4.0.0/include/
results in
error: __float128 is not supported on this target.
This persists after removing the corresponding lines from c++config.h as suggested on stackoverflow.
Set gcc as compiler with
export CC=/usr/local/bin/gcc-7.
This should work out of the box, but throws
cc-7: error: unrecognized command line option '-Wshorten-64-to-32'
independent of whether we use OpenMP or not. More about this error on stackoverflow
Seems to be solved here. Not sure how to apply this.