amazaspshumik / sklearn-bayes Goto Github PK
View Code? Open in Web Editor NEWPython package for Bayesian Machine Learning with scikit-learn API
License: MIT License
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alexyurasov jlopezpena bayesianhuman ferrine ltyscu jonathf karn09 turgunyusuf kumatty datnamer oncoimmunity weijifenstudent lizhangzhan hpgsantos andreas-koukorinis hoardboard lovedeer4ever benjamesbabala leezqcst stry makokal ruting1 nunofernandes-plight mizi1993 galvin-mj sophiegif philippmuench a-pai mjabri anirband tonywang1990 triplekill pharrellwang rileysparsons grseb9s adesh kurnianggoro mikeaddison93 jizhihang manuelschmidt davidlibland joefowler gelazari hoangcuong2011 ariapharmaceuticals mark0935git yjian180 athon-millane masonic9 clustersdata rchen14 pkmklong testudinate mindis sohuking66 wjjayst2008 chabobo chen-xu-0812 lli27 vishalbelsare shlpu fangp yutiansut td-2018 qingyunsun charie411 afan1018 afcarl ko-fujita energylulu birajaghoshal ylf-li hucklebery shengquanchen lile-tju basem-ahmed serenidpity joshuaze limingbei alvis-huang mrking0813 starjf miloventimiglia mark-dev-data-sci melodykxq zhaobin-li sarrme mskarlinski-ww ashishpatel26 xavisuau thaipduong durbin-watson yexiangyan martinhavlicek alex7088 khoalx nevesz xiaozhimabing helloheshee hongirsasklearn-bayes's Issues
Print relevance vectors to screen
Can someone help me print the non-zero weights to screen so I can determine the relevance vectors?
Thanks
K
ARD and RVM regressions: Convergence
Hi,
thank you for the code, it was very easy to use and seems to work fine!
I just have a small question: I am using the regression tools, and it seems that in your first example (sinc) the algorithm stops way before the actual convergence, because the default number of iterations is 300. By forcing more iterations I obtain:
RVR(coef0=1, copy_X=True, degree=3, fit_intercept=True, gamma=1, kernel='rbf',
kernel_params=None, n_iter=10000, tol=0.001, verbose=True)
gives : Iteration: 1537, number of features in the model: 9
Algorithm converged !
Is it to be expect to have that much number of iterations? If so, do you think the approximation at 100 or 300 iterations is valid?
Thank you!!
Ipython notebooks for bernoulli mixture models.
You have some cool ipython notebooks for implemented models but I did not found anything for bernoulli mixture model. Is it just me or there is no notebooks on bmm?
Question on RVM implementation details
Hi, Amazasp Shumik,
The fast rvm implementation is fantastic, and I learn a lot from your codes. Umm, I have a few question on the implementation details:
1.
2.
So, the calculation of Qm and t hat seems different from the original paper, is it some kind of approximation, and how to deduce them? thx.
Cannot install on OS X 10.15
I get the following errors when trying to install
(venv) simone ~/PycharmProjects/project $ pip install Cython
Collecting Cython
Downloading Cython-0.29.21-cp37-cp37m-macosx_10_9_x86_64.whl (1.9 MB)
|████████████████████████████████| 1.9 MB 1.3 MB/s
Installing collected packages: Cython
Successfully installed Cython-0.29.21
WARNING: You are using pip version 20.2.4; however, version 20.3.3 is available.
You should consider upgrading via the '/Users/simone/PycharmProjects/project/venv/bin/python -m pip install --upgrade pip' command.
(venv) simone ~/PycharmProjects/project $ pip install https://github.com/AmazaspShumik/sklearn_bayes/archive/master.zip
Collecting https://github.com/AmazaspShumik/sklearn_bayes/archive/master.zip
Downloading https://github.com/AmazaspShumik/sklearn_bayes/archive/master.zip
\ 4.3 MB 255 kB/s
Requirement already satisfied: numpy>=1.9.2 in ./venv/lib/python3.7/site-packages (from skbayes==0.1.0a1) (1.18.5)
Requirement already satisfied: scipy>=0.15.1 in ./venv/lib/python3.7/site-packages (from skbayes==0.1.0a1) (1.5.4)
Requirement already satisfied: scikit-learn>=0.17 in ./venv/lib/python3.7/site-packages (from skbayes==0.1.0a1) (0.23.2)
Requirement already satisfied: cython>=0.24 in ./venv/lib/python3.7/site-packages (from skbayes==0.1.0a1) (0.29.21)
Requirement already satisfied: threadpoolctl>=2.0.0 in ./venv/lib/python3.7/site-packages (from scikit-learn>=0.17->skbayes==0.1.0a1) (2.1.0)
Requirement already satisfied: joblib>=0.11 in ./venv/lib/python3.7/site-packages (from scikit-learn>=0.17->skbayes==0.1.0a1) (0.17.0)
Building wheels for collected packages: skbayes
Building wheel for skbayes (setup.py) ... error
ERROR: Command errored out with exit status 1:
command: /Users/simone/PycharmProjects/project/venv/bin/python -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/private/var/folders/dj/krrkt8p95qndhg46m2n774d80000gn/T/pip-req-build-97u7n087/setup.py'"'"'; __file__='"'"'/private/var/folders/dj/krrkt8p95qndhg46m2n774d80000gn/T/pip-req-build-97u7n087/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' bdist_wheel -d /private/var/folders/dj/krrkt8p95qndhg46m2n774d80000gn/T/pip-wheel-94r0n98w
cwd: /private/var/folders/dj/krrkt8p95qndhg46m2n774d80000gn/T/pip-req-build-97u7n087/
Complete output (275 lines):
running bdist_wheel
running build
running build_py
creating build
creating build/lib.macosx-10.15-x86_64-3.7
creating build/lib.macosx-10.15-x86_64-3.7/skbayes
copying skbayes/__init__.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes
creating build/lib.macosx-10.15-x86_64-3.7/skbayes/decomposition_models
copying skbayes/decomposition_models/__init__.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/decomposition_models
copying skbayes/decomposition_models/rbm.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/decomposition_models
creating build/lib.macosx-10.15-x86_64-3.7/skbayes/mixture_models
copying skbayes/mixture_models/dpmixture.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/mixture_models
copying skbayes/mixture_models/mixture.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/mixture_models
copying skbayes/mixture_models/__init__.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/mixture_models
creating build/lib.macosx-10.15-x86_64-3.7/skbayes/hidden_markov_models
copying skbayes/hidden_markov_models/__init__.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/hidden_markov_models
creating build/lib.macosx-10.15-x86_64-3.7/skbayes/rvm_ard_models
copying skbayes/rvm_ard_models/fast_rvm.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/rvm_ard_models
copying skbayes/rvm_ard_models/__init__.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/rvm_ard_models
copying skbayes/rvm_ard_models/vrvm.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/rvm_ard_models
creating build/lib.macosx-10.15-x86_64-3.7/skbayes/linear_models
copying skbayes/linear_models/bayes_logistic.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/linear_models
copying skbayes/linear_models/__init__.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/linear_models
copying skbayes/linear_models/bayes_linear.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/linear_models
running build_ext
building 'skbayes.decomposition_models.gibbs_lda_cython' extension
Warning: Can't read registry to find the necessary compiler setting
Make sure that Python modules winreg, win32api or win32con are installed.
C compiler: clang -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -I/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/include -I/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/include
creating build/temp.macosx-10.15-x86_64-3.7
creating build/temp.macosx-10.15-x86_64-3.7/skbayes
creating build/temp.macosx-10.15-x86_64-3.7/skbayes/decomposition_models
compile options: '-I/Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include -I/Users/simone/PycharmProjects/project/venv/include -I/Users/simone/.pyenv/versions/3.7.3/include/python3.7m -c'
extra options: '-O3'
clang: skbayes/decomposition_models/gibbs_lda_cython.c
In file included from skbayes/decomposition_models/gibbs_lda_cython.c:280:
In file included from /Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/arrayobject.h:4:
In file included from /Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:12:
In file included from /Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1832:
/Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-W#warnings]
#warning "Using deprecated NumPy API, disable it with " \
^
In file included from skbayes/decomposition_models/gibbs_lda_cython.c:280:
In file included from /Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/arrayobject.h:4:
In file included from /Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:21:
/Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/__multiarray_api.h:1463:1: warning: unused function '_import_array' [-Wunused-function]
_import_array(void)
^
skbayes/decomposition_models/gibbs_lda_cython.c:15698:28: warning: unused function '__Pyx_PyObject_AsString' [-Wunused-function]
static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject* o) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15695:32: warning: unused function '__Pyx_PyUnicode_FromString' [-Wunused-function]
static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15810:33: warning: unused function '__Pyx_PyIndex_AsSsize_t' [-Wunused-function]
static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15872:33: warning: unused function '__Pyx_PyInt_FromSize_t' [-Wunused-function]
static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:13196:32: warning: unused function '__Pyx_GetItemInt_List_Fast' [-Wunused-function]
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i,
^
skbayes/decomposition_models/gibbs_lda_cython.c:13211:32: warning: unused function '__Pyx_GetItemInt_Tuple_Fast' [-Wunused-function]
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i,
^
skbayes/decomposition_models/gibbs_lda_cython.c:14404:28: warning: unused function '__Pyx_CyFunction_InitDefaults' [-Wunused-function]
static CYTHON_INLINE void *__Pyx_CyFunction_InitDefaults(PyObject *func, size_t size, int pyobjects) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14418:27: warning: unused function '__Pyx_CyFunction_SetDefaultsKwDict' [-Wunused-function]
static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsKwDict(PyObject *func, PyObject *dict) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14423:27: warning: unused function '__Pyx_CyFunction_SetAnnotationsDict' [-Wunused-function]
static CYTHON_INLINE void __Pyx_CyFunction_SetAnnotationsDict(PyObject *func, PyObject *dict) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14899:48: warning: unused function '__pyx_t_float_complex_from_parts' [-Wunused-function]
static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14910:30: warning: unused function '__Pyx_c_eqf' [-Wunused-function]
static CYTHON_INLINE int __Pyx_c_eqf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14913:48: warning: unused function '__Pyx_c_sumf' [-Wunused-function]
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sumf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14919:48: warning: unused function '__Pyx_c_difff' [-Wunused-function]
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_difff(__pyx_t_float_complex a, __pyx_t_float_complex b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14931:48: warning: unused function '__Pyx_c_quotf' [-Wunused-function]
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quotf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14938:48: warning: unused function '__Pyx_c_negf' [-Wunused-function]
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_negf(__pyx_t_float_complex a) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14944:30: warning: unused function '__Pyx_c_is_zerof' [-Wunused-function]
static CYTHON_INLINE int __Pyx_c_is_zerof(__pyx_t_float_complex a) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14947:48: warning: unused function '__Pyx_c_conjf' [-Wunused-function]
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conjf(__pyx_t_float_complex a) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14961:52: warning: unused function '__Pyx_c_powf' [-Wunused-function]
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_powf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15021:49: warning: unused function '__pyx_t_double_complex_from_parts' [-Wunused-function]
static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15032:30: warning: unused function '__Pyx_c_eq' [-Wunused-function]
static CYTHON_INLINE int __Pyx_c_eq(__pyx_t_double_complex a, __pyx_t_double_complex b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15035:49: warning: unused function '__Pyx_c_sum' [-Wunused-function]
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum(__pyx_t_double_complex a, __pyx_t_double_complex b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15041:49: warning: unused function '__Pyx_c_diff' [-Wunused-function]
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff(__pyx_t_double_complex a, __pyx_t_double_complex b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15053:49: warning: unused function '__Pyx_c_quot' [-Wunused-function]
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot(__pyx_t_double_complex a, __pyx_t_double_complex b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15060:49: warning: unused function '__Pyx_c_neg' [-Wunused-function]
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg(__pyx_t_double_complex a) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15066:30: warning: unused function '__Pyx_c_is_zero' [-Wunused-function]
static CYTHON_INLINE int __Pyx_c_is_zero(__pyx_t_double_complex a) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15069:49: warning: unused function '__Pyx_c_conj' [-Wunused-function]
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj(__pyx_t_double_complex a) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15083:53: warning: unused function '__Pyx_c_pow' [-Wunused-function]
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow(__pyx_t_double_complex a, __pyx_t_double_complex b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:9832:32: warning: unused function '__pyx_f_5numpy_PyArray_MultiIterNew1' [-Wunused-function]
static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew1(PyObject *__pyx_v_a) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:9879:32: warning: unused function '__pyx_f_5numpy_PyArray_MultiIterNew2' [-Wunused-function]
static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew2(PyObject *__pyx_v_a, PyObject *__pyx_v_b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:9926:32: warning: unused function '__pyx_f_5numpy_PyArray_MultiIterNew3' [-Wunused-function]
static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew3(PyObject *__pyx_v_a, PyObject *__pyx_v_b, PyObject *__pyx_v_c) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:9973:32: warning: unused function '__pyx_f_5numpy_PyArray_MultiIterNew4' [-Wunused-function]
static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew4(PyObject *__pyx_v_a, PyObject *__pyx_v_b, PyObject *__pyx_v_c, PyObject *__pyx_v_d) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:10020:32: warning: unused function '__pyx_f_5numpy_PyArray_MultiIterNew5' [-Wunused-function]
static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew5(PyObject *__pyx_v_a, PyObject *__pyx_v_b, PyObject *__pyx_v_c, PyObject *__pyx_v_d, PyObject *__pyx_v_e) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:10822:27: warning: unused function '__pyx_f_5numpy_set_array_base' [-Wunused-function]
static CYTHON_INLINE void __pyx_f_5numpy_set_array_base(PyArrayObject *__pyx_v_arr, PyObject *__pyx_v_base) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:10918:32: warning: unused function '__pyx_f_5numpy_get_array_base' [-Wunused-function]
static CYTHON_INLINE PyObject *__pyx_f_5numpy_get_array_base(PyArrayObject *__pyx_v_arr) {
^
36 warnings generated.
clang -bundle -undefined dynamic_lookup -L/usr/local/opt/readline/lib -L/usr/local/opt/readline/lib -L/Users/simone/.pyenv/versions/3.7.3/lib -L/usr/local/opt/readline/lib -L/usr/local/opt/readline/lib -L/Users/simone/.pyenv/versions/3.7.3/lib build/temp.macosx-10.15-x86_64-3.7/skbayes/decomposition_models/gibbs_lda_cython.o -L/Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/lib -lnpymath -o build/lib.macosx-10.15-x86_64-3.7/skbayes/decomposition_models/gibbs_lda_cython.cpython-37m-darwin.so
building 'skbayes.hidden_markov_models.hmm' extension
C compiler: clang -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -I/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/include -I/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/include
creating build/temp.macosx-10.15-x86_64-3.7/skbayes/hidden_markov_models
compile options: '-I/Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include -I/Users/simone/PycharmProjects/project/venv/include -I/Users/simone/.pyenv/versions/3.7.3/include/python3.7m -c'
extra options: '-O3'
clang: skbayes/hidden_markov_models/hmm.c
In file included from skbayes/hidden_markov_models/hmm.c:280:
In file included from /Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/arrayobject.h:4:
In file included from /Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:12:
In file included from /Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1832:
/Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-W#warnings]
#warning "Using deprecated NumPy API, disable it with " \
^
skbayes/hidden_markov_models/hmm.c:28348:21: error: no member named 'exc_type' in 'struct _ts'
*type = tstate->exc_type;
~~~~~~ ^
skbayes/hidden_markov_models/hmm.c:28349:22: error: no member named 'exc_value' in 'struct _ts'; did you mean 'curexc_value'?
*value = tstate->exc_value;
^~~~~~~~~
curexc_value
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:240:15: note: 'curexc_value' declared here
PyObject *curexc_value;
^
skbayes/hidden_markov_models/hmm.c:28350:19: error: no member named 'exc_traceback' in 'struct _ts'; did you mean 'curexc_traceback'?
*tb = tstate->exc_traceback;
^~~~~~~~~~~~~
curexc_traceback
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:241:15: note: 'curexc_traceback' declared here
PyObject *curexc_traceback;
^
skbayes/hidden_markov_models/hmm.c:28357:24: error: no member named 'exc_type' in 'struct _ts'
tmp_type = tstate->exc_type;
~~~~~~ ^
skbayes/hidden_markov_models/hmm.c:28358:25: error: no member named 'exc_value' in 'struct _ts'; did you mean 'curexc_value'?
tmp_value = tstate->exc_value;
^~~~~~~~~
curexc_value
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:240:15: note: 'curexc_value' declared here
PyObject *curexc_value;
^
skbayes/hidden_markov_models/hmm.c:28359:22: error: no member named 'exc_traceback' in 'struct _ts'; did you mean 'curexc_traceback'?
tmp_tb = tstate->exc_traceback;
^~~~~~~~~~~~~
curexc_traceback
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:241:15: note: 'curexc_traceback' declared here
PyObject *curexc_traceback;
^
skbayes/hidden_markov_models/hmm.c:28360:13: error: no member named 'exc_type' in 'struct _ts'
tstate->exc_type = type;
~~~~~~ ^
skbayes/hidden_markov_models/hmm.c:28361:13: error: no member named 'exc_value' in 'struct _ts'; did you mean 'curexc_value'?
tstate->exc_value = value;
^~~~~~~~~
curexc_value
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:240:15: note: 'curexc_value' declared here
PyObject *curexc_value;
^
skbayes/hidden_markov_models/hmm.c:28362:13: error: no member named 'exc_traceback' in 'struct _ts'; did you mean 'curexc_traceback'?
tstate->exc_traceback = tb;
^~~~~~~~~~~~~
curexc_traceback
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:241:15: note: 'curexc_traceback' declared here
PyObject *curexc_traceback;
^
skbayes/hidden_markov_models/hmm.c:28407:24: error: no member named 'exc_type' in 'struct _ts'
tmp_type = tstate->exc_type;
~~~~~~ ^
skbayes/hidden_markov_models/hmm.c:28408:25: error: no member named 'exc_value' in 'struct _ts'; did you mean 'curexc_value'?
tmp_value = tstate->exc_value;
^~~~~~~~~
curexc_value
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:240:15: note: 'curexc_value' declared here
PyObject *curexc_value;
^
skbayes/hidden_markov_models/hmm.c:28409:22: error: no member named 'exc_traceback' in 'struct _ts'; did you mean 'curexc_traceback'?
tmp_tb = tstate->exc_traceback;
^~~~~~~~~~~~~
curexc_traceback
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:241:15: note: 'curexc_traceback' declared here
PyObject *curexc_traceback;
^
skbayes/hidden_markov_models/hmm.c:28410:13: error: no member named 'exc_type' in 'struct _ts'
tstate->exc_type = local_type;
~~~~~~ ^
skbayes/hidden_markov_models/hmm.c:28411:13: error: no member named 'exc_value' in 'struct _ts'; did you mean 'curexc_value'?
tstate->exc_value = local_value;
^~~~~~~~~
curexc_value
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:240:15: note: 'curexc_value' declared here
PyObject *curexc_value;
^
skbayes/hidden_markov_models/hmm.c:28412:13: error: no member named 'exc_traceback' in 'struct _ts'; did you mean 'curexc_traceback'?
tstate->exc_traceback = local_tb;
^~~~~~~~~~~~~
curexc_traceback
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:241:15: note: 'curexc_traceback' declared here
PyObject *curexc_traceback;
^
skbayes/hidden_markov_models/hmm.c:30306:24: error: no member named 'exc_type' in 'struct _ts'
tmp_type = tstate->exc_type;
~~~~~~ ^
skbayes/hidden_markov_models/hmm.c:30307:25: error: no member named 'exc_value' in 'struct _ts'; did you mean 'curexc_value'?
tmp_value = tstate->exc_value;
^~~~~~~~~
curexc_value
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:240:15: note: 'curexc_value' declared here
PyObject *curexc_value;
^
skbayes/hidden_markov_models/hmm.c:30308:22: error: no member named 'exc_traceback' in 'struct _ts'; did you mean 'curexc_traceback'?
tmp_tb = tstate->exc_traceback;
^~~~~~~~~~~~~
curexc_traceback
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:241:15: note: 'curexc_traceback' declared here
PyObject *curexc_traceback;
^
skbayes/hidden_markov_models/hmm.c:30309:13: error: no member named 'exc_type' in 'struct _ts'
tstate->exc_type = *type;
~~~~~~ ^
fatal error: too many errors emitted, stopping now [-ferror-limit=]
1 warning and 20 errors generated.
error: Command "clang -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -I/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/include -I/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/include -I/Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include -I/Users/simone/PycharmProjects/project/venv/include -I/Users/simone/.pyenv/versions/3.7.3/include/python3.7m -c skbayes/hidden_markov_models/hmm.c -o build/temp.macosx-10.15-x86_64-3.7/skbayes/hidden_markov_models/hmm.o -O3" failed with exit status 1
----------------------------------------
ERROR: Failed building wheel for skbayes
Running setup.py clean for skbayes
Failed to build skbayes
Installing collected packages: skbayes
Running setup.py install for skbayes ... error
ERROR: Command errored out with exit status 1:
command: /Users/simone/PycharmProjects/project/venv/bin/python -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/private/var/folders/dj/krrkt8p95qndhg46m2n774d80000gn/T/pip-req-build-97u7n087/setup.py'"'"'; __file__='"'"'/private/var/folders/dj/krrkt8p95qndhg46m2n774d80000gn/T/pip-req-build-97u7n087/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record /private/var/folders/dj/krrkt8p95qndhg46m2n774d80000gn/T/pip-record-5k3krs1g/install-record.txt --single-version-externally-managed --compile --install-headers /Users/simone/PycharmProjects/project/venv/include/site/python3.7/skbayes
cwd: /private/var/folders/dj/krrkt8p95qndhg46m2n774d80000gn/T/pip-req-build-97u7n087/
Complete output (275 lines):
running install
running build
running build_py
creating build
creating build/lib.macosx-10.15-x86_64-3.7
creating build/lib.macosx-10.15-x86_64-3.7/skbayes
copying skbayes/__init__.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes
creating build/lib.macosx-10.15-x86_64-3.7/skbayes/decomposition_models
copying skbayes/decomposition_models/__init__.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/decomposition_models
copying skbayes/decomposition_models/rbm.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/decomposition_models
creating build/lib.macosx-10.15-x86_64-3.7/skbayes/mixture_models
copying skbayes/mixture_models/dpmixture.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/mixture_models
copying skbayes/mixture_models/mixture.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/mixture_models
copying skbayes/mixture_models/__init__.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/mixture_models
creating build/lib.macosx-10.15-x86_64-3.7/skbayes/hidden_markov_models
copying skbayes/hidden_markov_models/__init__.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/hidden_markov_models
creating build/lib.macosx-10.15-x86_64-3.7/skbayes/rvm_ard_models
copying skbayes/rvm_ard_models/fast_rvm.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/rvm_ard_models
copying skbayes/rvm_ard_models/__init__.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/rvm_ard_models
copying skbayes/rvm_ard_models/vrvm.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/rvm_ard_models
creating build/lib.macosx-10.15-x86_64-3.7/skbayes/linear_models
copying skbayes/linear_models/bayes_logistic.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/linear_models
copying skbayes/linear_models/__init__.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/linear_models
copying skbayes/linear_models/bayes_linear.py -> build/lib.macosx-10.15-x86_64-3.7/skbayes/linear_models
running build_ext
building 'skbayes.decomposition_models.gibbs_lda_cython' extension
Warning: Can't read registry to find the necessary compiler setting
Make sure that Python modules winreg, win32api or win32con are installed.
C compiler: clang -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -I/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/include -I/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/include
creating build/temp.macosx-10.15-x86_64-3.7
creating build/temp.macosx-10.15-x86_64-3.7/skbayes
creating build/temp.macosx-10.15-x86_64-3.7/skbayes/decomposition_models
compile options: '-I/Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include -I/Users/simone/PycharmProjects/project/venv/include -I/Users/simone/.pyenv/versions/3.7.3/include/python3.7m -c'
extra options: '-O3'
clang: skbayes/decomposition_models/gibbs_lda_cython.c
In file included from skbayes/decomposition_models/gibbs_lda_cython.c:280:
In file included from /Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/arrayobject.h:4:
In file included from /Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:12:
In file included from /Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1832:
/Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-W#warnings]
#warning "Using deprecated NumPy API, disable it with " \
^
In file included from skbayes/decomposition_models/gibbs_lda_cython.c:280:
In file included from /Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/arrayobject.h:4:
In file included from /Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:21:
/Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/__multiarray_api.h:1463:1: warning: unused function '_import_array' [-Wunused-function]
_import_array(void)
^
skbayes/decomposition_models/gibbs_lda_cython.c:15698:28: warning: unused function '__Pyx_PyObject_AsString' [-Wunused-function]
static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject* o) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15695:32: warning: unused function '__Pyx_PyUnicode_FromString' [-Wunused-function]
static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15810:33: warning: unused function '__Pyx_PyIndex_AsSsize_t' [-Wunused-function]
static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15872:33: warning: unused function '__Pyx_PyInt_FromSize_t' [-Wunused-function]
static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:13196:32: warning: unused function '__Pyx_GetItemInt_List_Fast' [-Wunused-function]
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i,
^
skbayes/decomposition_models/gibbs_lda_cython.c:13211:32: warning: unused function '__Pyx_GetItemInt_Tuple_Fast' [-Wunused-function]
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i,
^
skbayes/decomposition_models/gibbs_lda_cython.c:14404:28: warning: unused function '__Pyx_CyFunction_InitDefaults' [-Wunused-function]
static CYTHON_INLINE void *__Pyx_CyFunction_InitDefaults(PyObject *func, size_t size, int pyobjects) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14418:27: warning: unused function '__Pyx_CyFunction_SetDefaultsKwDict' [-Wunused-function]
static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsKwDict(PyObject *func, PyObject *dict) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14423:27: warning: unused function '__Pyx_CyFunction_SetAnnotationsDict' [-Wunused-function]
static CYTHON_INLINE void __Pyx_CyFunction_SetAnnotationsDict(PyObject *func, PyObject *dict) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14899:48: warning: unused function '__pyx_t_float_complex_from_parts' [-Wunused-function]
static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14910:30: warning: unused function '__Pyx_c_eqf' [-Wunused-function]
static CYTHON_INLINE int __Pyx_c_eqf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14913:48: warning: unused function '__Pyx_c_sumf' [-Wunused-function]
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sumf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14919:48: warning: unused function '__Pyx_c_difff' [-Wunused-function]
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_difff(__pyx_t_float_complex a, __pyx_t_float_complex b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14931:48: warning: unused function '__Pyx_c_quotf' [-Wunused-function]
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quotf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14938:48: warning: unused function '__Pyx_c_negf' [-Wunused-function]
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_negf(__pyx_t_float_complex a) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14944:30: warning: unused function '__Pyx_c_is_zerof' [-Wunused-function]
static CYTHON_INLINE int __Pyx_c_is_zerof(__pyx_t_float_complex a) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14947:48: warning: unused function '__Pyx_c_conjf' [-Wunused-function]
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conjf(__pyx_t_float_complex a) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:14961:52: warning: unused function '__Pyx_c_powf' [-Wunused-function]
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_powf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15021:49: warning: unused function '__pyx_t_double_complex_from_parts' [-Wunused-function]
static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15032:30: warning: unused function '__Pyx_c_eq' [-Wunused-function]
static CYTHON_INLINE int __Pyx_c_eq(__pyx_t_double_complex a, __pyx_t_double_complex b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15035:49: warning: unused function '__Pyx_c_sum' [-Wunused-function]
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum(__pyx_t_double_complex a, __pyx_t_double_complex b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15041:49: warning: unused function '__Pyx_c_diff' [-Wunused-function]
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff(__pyx_t_double_complex a, __pyx_t_double_complex b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15053:49: warning: unused function '__Pyx_c_quot' [-Wunused-function]
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot(__pyx_t_double_complex a, __pyx_t_double_complex b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15060:49: warning: unused function '__Pyx_c_neg' [-Wunused-function]
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg(__pyx_t_double_complex a) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15066:30: warning: unused function '__Pyx_c_is_zero' [-Wunused-function]
static CYTHON_INLINE int __Pyx_c_is_zero(__pyx_t_double_complex a) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15069:49: warning: unused function '__Pyx_c_conj' [-Wunused-function]
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj(__pyx_t_double_complex a) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:15083:53: warning: unused function '__Pyx_c_pow' [-Wunused-function]
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow(__pyx_t_double_complex a, __pyx_t_double_complex b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:9832:32: warning: unused function '__pyx_f_5numpy_PyArray_MultiIterNew1' [-Wunused-function]
static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew1(PyObject *__pyx_v_a) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:9879:32: warning: unused function '__pyx_f_5numpy_PyArray_MultiIterNew2' [-Wunused-function]
static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew2(PyObject *__pyx_v_a, PyObject *__pyx_v_b) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:9926:32: warning: unused function '__pyx_f_5numpy_PyArray_MultiIterNew3' [-Wunused-function]
static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew3(PyObject *__pyx_v_a, PyObject *__pyx_v_b, PyObject *__pyx_v_c) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:9973:32: warning: unused function '__pyx_f_5numpy_PyArray_MultiIterNew4' [-Wunused-function]
static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew4(PyObject *__pyx_v_a, PyObject *__pyx_v_b, PyObject *__pyx_v_c, PyObject *__pyx_v_d) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:10020:32: warning: unused function '__pyx_f_5numpy_PyArray_MultiIterNew5' [-Wunused-function]
static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew5(PyObject *__pyx_v_a, PyObject *__pyx_v_b, PyObject *__pyx_v_c, PyObject *__pyx_v_d, PyObject *__pyx_v_e) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:10822:27: warning: unused function '__pyx_f_5numpy_set_array_base' [-Wunused-function]
static CYTHON_INLINE void __pyx_f_5numpy_set_array_base(PyArrayObject *__pyx_v_arr, PyObject *__pyx_v_base) {
^
skbayes/decomposition_models/gibbs_lda_cython.c:10918:32: warning: unused function '__pyx_f_5numpy_get_array_base' [-Wunused-function]
static CYTHON_INLINE PyObject *__pyx_f_5numpy_get_array_base(PyArrayObject *__pyx_v_arr) {
^
36 warnings generated.
clang -bundle -undefined dynamic_lookup -L/usr/local/opt/readline/lib -L/usr/local/opt/readline/lib -L/Users/simone/.pyenv/versions/3.7.3/lib -L/usr/local/opt/readline/lib -L/usr/local/opt/readline/lib -L/Users/simone/.pyenv/versions/3.7.3/lib build/temp.macosx-10.15-x86_64-3.7/skbayes/decomposition_models/gibbs_lda_cython.o -L/Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/lib -lnpymath -o build/lib.macosx-10.15-x86_64-3.7/skbayes/decomposition_models/gibbs_lda_cython.cpython-37m-darwin.so
building 'skbayes.hidden_markov_models.hmm' extension
C compiler: clang -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -I/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/include -I/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/include
creating build/temp.macosx-10.15-x86_64-3.7/skbayes/hidden_markov_models
compile options: '-I/Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include -I/Users/simone/PycharmProjects/project/venv/include -I/Users/simone/.pyenv/versions/3.7.3/include/python3.7m -c'
extra options: '-O3'
clang: skbayes/hidden_markov_models/hmm.c
In file included from skbayes/hidden_markov_models/hmm.c:280:
In file included from /Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/arrayobject.h:4:
In file included from /Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:12:
In file included from /Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1832:
/Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-W#warnings]
#warning "Using deprecated NumPy API, disable it with " \
^
skbayes/hidden_markov_models/hmm.c:28348:21: error: no member named 'exc_type' in 'struct _ts'
*type = tstate->exc_type;
~~~~~~ ^
skbayes/hidden_markov_models/hmm.c:28349:22: error: no member named 'exc_value' in 'struct _ts'; did you mean 'curexc_value'?
*value = tstate->exc_value;
^~~~~~~~~
curexc_value
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:240:15: note: 'curexc_value' declared here
PyObject *curexc_value;
^
skbayes/hidden_markov_models/hmm.c:28350:19: error: no member named 'exc_traceback' in 'struct _ts'; did you mean 'curexc_traceback'?
*tb = tstate->exc_traceback;
^~~~~~~~~~~~~
curexc_traceback
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:241:15: note: 'curexc_traceback' declared here
PyObject *curexc_traceback;
^
skbayes/hidden_markov_models/hmm.c:28357:24: error: no member named 'exc_type' in 'struct _ts'
tmp_type = tstate->exc_type;
~~~~~~ ^
skbayes/hidden_markov_models/hmm.c:28358:25: error: no member named 'exc_value' in 'struct _ts'; did you mean 'curexc_value'?
tmp_value = tstate->exc_value;
^~~~~~~~~
curexc_value
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:240:15: note: 'curexc_value' declared here
PyObject *curexc_value;
^
skbayes/hidden_markov_models/hmm.c:28359:22: error: no member named 'exc_traceback' in 'struct _ts'; did you mean 'curexc_traceback'?
tmp_tb = tstate->exc_traceback;
^~~~~~~~~~~~~
curexc_traceback
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:241:15: note: 'curexc_traceback' declared here
PyObject *curexc_traceback;
^
skbayes/hidden_markov_models/hmm.c:28360:13: error: no member named 'exc_type' in 'struct _ts'
tstate->exc_type = type;
~~~~~~ ^
skbayes/hidden_markov_models/hmm.c:28361:13: error: no member named 'exc_value' in 'struct _ts'; did you mean 'curexc_value'?
tstate->exc_value = value;
^~~~~~~~~
curexc_value
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:240:15: note: 'curexc_value' declared here
PyObject *curexc_value;
^
skbayes/hidden_markov_models/hmm.c:28362:13: error: no member named 'exc_traceback' in 'struct _ts'; did you mean 'curexc_traceback'?
tstate->exc_traceback = tb;
^~~~~~~~~~~~~
curexc_traceback
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:241:15: note: 'curexc_traceback' declared here
PyObject *curexc_traceback;
^
skbayes/hidden_markov_models/hmm.c:28407:24: error: no member named 'exc_type' in 'struct _ts'
tmp_type = tstate->exc_type;
~~~~~~ ^
skbayes/hidden_markov_models/hmm.c:28408:25: error: no member named 'exc_value' in 'struct _ts'; did you mean 'curexc_value'?
tmp_value = tstate->exc_value;
^~~~~~~~~
curexc_value
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:240:15: note: 'curexc_value' declared here
PyObject *curexc_value;
^
skbayes/hidden_markov_models/hmm.c:28409:22: error: no member named 'exc_traceback' in 'struct _ts'; did you mean 'curexc_traceback'?
tmp_tb = tstate->exc_traceback;
^~~~~~~~~~~~~
curexc_traceback
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:241:15: note: 'curexc_traceback' declared here
PyObject *curexc_traceback;
^
skbayes/hidden_markov_models/hmm.c:28410:13: error: no member named 'exc_type' in 'struct _ts'
tstate->exc_type = local_type;
~~~~~~ ^
skbayes/hidden_markov_models/hmm.c:28411:13: error: no member named 'exc_value' in 'struct _ts'; did you mean 'curexc_value'?
tstate->exc_value = local_value;
^~~~~~~~~
curexc_value
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:240:15: note: 'curexc_value' declared here
PyObject *curexc_value;
^
skbayes/hidden_markov_models/hmm.c:28412:13: error: no member named 'exc_traceback' in 'struct _ts'; did you mean 'curexc_traceback'?
tstate->exc_traceback = local_tb;
^~~~~~~~~~~~~
curexc_traceback
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:241:15: note: 'curexc_traceback' declared here
PyObject *curexc_traceback;
^
skbayes/hidden_markov_models/hmm.c:30306:24: error: no member named 'exc_type' in 'struct _ts'
tmp_type = tstate->exc_type;
~~~~~~ ^
skbayes/hidden_markov_models/hmm.c:30307:25: error: no member named 'exc_value' in 'struct _ts'; did you mean 'curexc_value'?
tmp_value = tstate->exc_value;
^~~~~~~~~
curexc_value
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:240:15: note: 'curexc_value' declared here
PyObject *curexc_value;
^
skbayes/hidden_markov_models/hmm.c:30308:22: error: no member named 'exc_traceback' in 'struct _ts'; did you mean 'curexc_traceback'?
tmp_tb = tstate->exc_traceback;
^~~~~~~~~~~~~
curexc_traceback
/Users/simone/.pyenv/versions/3.7.3/include/python3.7m/pystate.h:241:15: note: 'curexc_traceback' declared here
PyObject *curexc_traceback;
^
skbayes/hidden_markov_models/hmm.c:30309:13: error: no member named 'exc_type' in 'struct _ts'
tstate->exc_type = *type;
~~~~~~ ^
fatal error: too many errors emitted, stopping now [-ferror-limit=]
1 warning and 20 errors generated.
error: Command "clang -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -I/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/include -I/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/include -I/Users/simone/PycharmProjects/project/venv/lib/python3.7/site-packages/numpy/core/include -I/Users/simone/PycharmProjects/project/venv/include -I/Users/simone/.pyenv/versions/3.7.3/include/python3.7m -c skbayes/hidden_markov_models/hmm.c -o build/temp.macosx-10.15-x86_64-3.7/skbayes/hidden_markov_models/hmm.o -O3" failed with exit status 1
----------------------------------------
ERROR: Command errored out with exit status 1: /Users/simone/PycharmProjects/project/venv/bin/python -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/private/var/folders/dj/krrkt8p95qndhg46m2n774d80000gn/T/pip-req-build-97u7n087/setup.py'"'"'; __file__='"'"'/private/var/folders/dj/krrkt8p95qndhg46m2n774d80000gn/T/pip-req-build-97u7n087/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record /private/var/folders/dj/krrkt8p95qndhg46m2n774d80000gn/T/pip-record-5k3krs1g/install-record.txt --single-version-externally-managed --compile --install-headers /Users/simone/PycharmProjects/project/venv/include/site/python3.7/skbayes Check the logs for full command output.
My env
OS X 10.15.6
Python 3.7.3
numpy==1.18.5
Apple clang version 12.0.0 (clang-1200.0.32.21)
Installation Fails on OSX 10.12.5 using Anaconda py2.7
Tried installing both from pip and using setup.py, got the following error message:
clang: error: linker command failed with exit code 1 (use -v to see invocation)
error: Command "/usr/bin/clang -bundle -undefined dynamic_lookup -arch i386 -arch x86_64 -g build/temp.macosx-10.6-intel-2.7/skbayes/decomposition_models/gibbs_lda_cython.o -L/usr/local/lib/python2.7/site-packages/numpy/core/lib -lnpymath -o build/lib.macosx-10.6-intel-2.7/skbayes/decomposition_models/gibbs_lda_cython.so" failed with exit status 1
'EBLinearRegression' object has no attribute '_center_data'
Hello,
I'm trying to use skbayes with the latest scikit-learn (0.18.x). It looks like self._center_data is no longer being used in sklearn:
from skbayes.linear_models import EBLinearRegression
EB = EBLinearRegression()
EB.fit(X,y)
Traceback (most recent call last):
File "<ipython-input-30-cd5ea38985d5>", line 1, in <module>
EB.fit(X,y)
File "C:\Anaconda2\lib\site-packages\skbayes\linear_models\bayesian_regression.py", line 102, in fit
X, y, X_mean, y_mean, X_std = self._center_data(X, y, self.fit_intercept,
AttributeError: 'EBLinearRegression' object has no attribute '_center_data'
Add Gaussian Mixture Emissions for VBHMM
Since there's already a Bayesian Mixture model implementation, it would be great if someone could extend the HMM implementation to include mixture emissions.
On a side note, is the n_hidden parameter in the HMM model deterministic or a maximum ala truncated HDP-HMM models? If the former, automatic state discovery would be nice but probably a lot more work.
Comparison of GMM with sklearn
I saw you implemented bayesian GMMs that are also in scikit-learn. Have you checked out the new versions? How do they compare to yours?
Variational Logistic Regression is too slow!
I was comparing Variational Logistic Regression and Relevance Vector Classifier, and though RVC seems to be more complicated model it is much faster to fit than Variational Bayesian Logistic Regression? Is there any implementation problems?
Non positive definite matrix (posterior of weights)
installation in windows 10 fails
great code thanks but
installation in windows 10 fails
Microsoft Windows [Version 10.0.17134.1130]
(c) 2018 Microsoft Corporation. All rights reserved.
D:\code\abcd\pip install https://github.com/AmazaspShumik/sklearn_bayes/archive/master.zip
Collecting https://github.com/AmazaspShumik/sklearn_bayes/archive/master.zip
Downloading https://github.com/AmazaspShumik/sklearn_bayes/archive/master.zip
- 5.8MB 2.2MB/s
Requirement already satisfied: numpy>=1.9.2 in c:\users\ABCDFG\appdata\local\continuum\anaconda3\lib\site-packages (from skbayes==0.1.0a1) (1.17.3)
Requirement already satisfied: scipy>=0.15.1 in c:\users\ABCDFG\appdata\local\continuum\anaconda3\lib\site-packages (from skbayes==0.1.0a1) (1.1.0)
Requirement already satisfied: scikit-learn>=0.17 in c:\users\ABCDFG\appdata\local\continuum\anaconda3\lib\site-packages (from skbayes==0.1.0a1) (0.21.3)
Requirement already satisfied: cython>=0.24 in c:\users\ABCDFG\appdata\local\continuum\anaconda3\lib\site-packages (from skbayes==0.1.0a1) (0.28.2)
Requirement already satisfied: joblib>=0.11 in c:\users\ABCDFG\appdata\local\continuum\anaconda3\lib\site-packages (from scikit-learn>=0.17->skbayes==0.1.0a1) (0.13.2)
Building wheels for collected packages: skbayes
Building wheel for skbayes (setup.py) ... error
ERROR: Complete output from command 'C:\Users\ABCDFG\AppData\Local\Continuum\anaconda3\python.exe' -u -c 'import setuptools, tokenize;__file__='"'"'C:\\Users\\ABCDFG\\AppData\\Local\\Temp\\pip-req-build-l568up61\\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' bdist_wheel -d 'C:\Users\ABCDFG\AppData\Local\Temp\pip-wheel-bl0aft0m' --python-tag cp36:
ERROR: running bdist_wheel
running build
running build_py
creating build
creating build\lib.win-amd64-3.6
creating build\lib.win-amd64-3.6\skbayes
copying skbayes\__init__.py -> build\lib.win-amd64-3.6\skbayes
creating build\lib.win-amd64-3.6\skbayes\decomposition_models
copying skbayes\decomposition_models\rbm.py -> build\lib.win-amd64-3.6\skbayes\decomposition_models
copying skbayes\decomposition_models\__init__.py -> build\lib.win-amd64-3.6\skbayes\decomposition_models
creating build\lib.win-amd64-3.6\skbayes\hidden_markov_models
copying skbayes\hidden_markov_models\__init__.py -> build\lib.win-amd64-3.6\skbayes\hidden_markov_models
creating build\lib.win-amd64-3.6\skbayes\linear_models
copying skbayes\linear_models\bayes_linear.py -> build\lib.win-amd64-3.6\skbayes\linear_models
copying skbayes\linear_models\bayes_logistic.py -> build\lib.win-amd64-3.6\skbayes\linear_models
copying skbayes\linear_models\__init__.py -> build\lib.win-amd64-3.6\skbayes\linear_models
creating build\lib.win-amd64-3.6\skbayes\mixture_models
copying skbayes\mixture_models\dpmixture.py -> build\lib.win-amd64-3.6\skbayes\mixture_models
copying skbayes\mixture_models\mixture.py -> build\lib.win-amd64-3.6\skbayes\mixture_models
copying skbayes\mixture_models\__init__.py -> build\lib.win-amd64-3.6\skbayes\mixture_models
creating build\lib.win-amd64-3.6\skbayes\rvm_ard_models
copying skbayes\rvm_ard_models\fast_rvm.py -> build\lib.win-amd64-3.6\skbayes\rvm_ard_models
copying skbayes\rvm_ard_models\vrvm.py -> build\lib.win-amd64-3.6\skbayes\rvm_ard_models
copying skbayes\rvm_ard_models\__init__.py -> build\lib.win-amd64-3.6\skbayes\rvm_ard_models
running build_ext
No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils
building 'skbayes.decomposition_models.gibbs_lda_cython' extension
creating build\temp.win-amd64-3.6
creating build\temp.win-amd64-3.6\Release
creating build\temp.win-amd64-3.6\Release\skbayes
creating build\temp.win-amd64-3.6\Release\skbayes\decomposition_models
cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -IC:\\Users\\ABCDFG\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\numpy\\core\\include -IC:\Users\ABCDFG\AppData\Local\Continuum\anaconda3\include -IC:\Users\ABCDFG\AppData\Local\Continuum\anaconda3\include /Tcskbayes/decomposition_models/gibbs_lda_cython.c /Fobuild\temp.win-amd64-3.6\Release\skbayes/decomposition_models/gibbs_lda_cython.obj -O3
error: Command "cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -IC:\\Users\\ABCDFG\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\numpy\\core\\include -IC:\Users\ABCDFG\AppData\Local\Continuum\anaconda3\include -IC:\Users\ABCDFG\AppData\Local\Continuum\anaconda3\include /Tcskbayes/decomposition_models/gibbs_lda_cython.c /Fobuild\temp.win-amd64-3.6\Release\skbayes/decomposition_models/gibbs_lda_cython.obj -O3" failed with exit status 127
----------------------------------------
ERROR: Failed building wheel for skbayes
Running setup.py clean for skbayes
Failed to build skbayes
Installing collected packages: skbayes
Running setup.py install for skbayes ... error
ERROR: Complete output from command 'C:\Users\ABCDFG\AppData\Local\Continuum\anaconda3\python.exe' -u -c 'import setuptools, tokenize;__file__='"'"'C:\\Users\\ABCDFG\\AppData\\Local\\Temp\\pip-req-build-l568up61\\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record 'C:\Users\ABCDFG\AppData\Local\Temp\pip-record-v7us44gt\install-record.txt' --single-version-externally-managed --compile:
ERROR: running install
running build
running build_py
creating build
creating build\lib.win-amd64-3.6
creating build\lib.win-amd64-3.6\skbayes
copying skbayes\__init__.py -> build\lib.win-amd64-3.6\skbayes
creating build\lib.win-amd64-3.6\skbayes\decomposition_models
copying skbayes\decomposition_models\rbm.py -> build\lib.win-amd64-3.6\skbayes\decomposition_models
copying skbayes\decomposition_models\__init__.py -> build\lib.win-amd64-3.6\skbayes\decomposition_models
creating build\lib.win-amd64-3.6\skbayes\hidden_markov_models
copying skbayes\hidden_markov_models\__init__.py -> build\lib.win-amd64-3.6\skbayes\hidden_markov_models
creating build\lib.win-amd64-3.6\skbayes\linear_models
copying skbayes\linear_models\bayes_linear.py -> build\lib.win-amd64-3.6\skbayes\linear_models
copying skbayes\linear_models\bayes_logistic.py -> build\lib.win-amd64-3.6\skbayes\linear_models
copying skbayes\linear_models\__init__.py -> build\lib.win-amd64-3.6\skbayes\linear_models
creating build\lib.win-amd64-3.6\skbayes\mixture_models
copying skbayes\mixture_models\dpmixture.py -> build\lib.win-amd64-3.6\skbayes\mixture_models
copying skbayes\mixture_models\mixture.py -> build\lib.win-amd64-3.6\skbayes\mixture_models
copying skbayes\mixture_models\__init__.py -> build\lib.win-amd64-3.6\skbayes\mixture_models
creating build\lib.win-amd64-3.6\skbayes\rvm_ard_models
copying skbayes\rvm_ard_models\fast_rvm.py -> build\lib.win-amd64-3.6\skbayes\rvm_ard_models
copying skbayes\rvm_ard_models\vrvm.py -> build\lib.win-amd64-3.6\skbayes\rvm_ard_models
copying skbayes\rvm_ard_models\__init__.py -> build\lib.win-amd64-3.6\skbayes\rvm_ard_models
running build_ext
No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils
building 'skbayes.decomposition_models.gibbs_lda_cython' extension
creating build\temp.win-amd64-3.6
creating build\temp.win-amd64-3.6\Release
creating build\temp.win-amd64-3.6\Release\skbayes
creating build\temp.win-amd64-3.6\Release\skbayes\decomposition_models
cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -IC:\\Users\\ABCDFG\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\numpy\\core\\include -IC:\Users\ABCDFG\AppData\Local\Continuum\anaconda3\include -IC:\Users\ABCDFG\AppData\Local\Continuum\anaconda3\include /Tcskbayes/decomposition_models/gibbs_lda_cython.c /Fobuild\temp.win-amd64-3.6\Release\skbayes/decomposition_models/gibbs_lda_cython.obj -O3
error: Command "cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -IC:\\Users\\ABCDFG\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\numpy\\core\\include -IC:\Users\ABCDFG\AppData\Local\Continuum\anaconda3\include -IC:\Users\ABCDFG\AppData\Local\Continuum\anaconda3\include /Tcskbayes/decomposition_models/gibbs_lda_cython.c /Fobuild\temp.win-amd64-3.6\Release\skbayes/decomposition_models/gibbs_lda_cython.obj -O3" failed with exit status 127
----------------------------------------
ERROR: Command "'C:\Users\ABCDFG\AppData\Local\Continuum\anaconda3\python.exe' -u -c 'import setuptools, tokenize;file='"'"'C:\Users\ABCDFG\AppData\Local\Temp\pip-req-build-l568up61\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(file);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, file, '"'"'exec'"'"'))' install --record 'C:\Users\ABCDFG\AppData\Local\Temp\pip-record-v7us44gt\install-record.txt' --single-version-externally-managed --compile" failed with error code 1 in C:\Users\ABCDFG\AppData\Local\Temp\pip-req-build-l568up61\
D:\code\abcd
Add warm start option
Some of the scikit-learn bayesian models include a warm_start parameter, where results of previous fit() calls are used as priors for the next fit. This would speed up any repeated or online inference without needing to resort to full SVI.
For example, in the mixture module it is implemented by skipping new initializations as follows:
do_init = not(self.warm_start and hasattr(self, 'converged_'))
(code from the mixture base class)
ARD and RVR: variance of predicitve distribution, take inverse?
Hello,
it seems that in the predict_dist functions, the variance output is calculated using this formula that seems true to me:
var=sigma^2+(K^T Sigma K)
In the code, sigma^2 (identified as alpha_) is directly the precision beta (in the fit method, self.alpha_ = beta). But the precision is usually the inverse of the variance (and seems to be calculated as the inverse of the variance, even in your initialization).
I think the code is good, just the predict_dist should be :
var_hat = 1./self.alpha_ ( and not var_hat = self._alpha)
var_hat += ...
If my thoughts are false, please do correct me!
Thank you again, I know looking back to your code must be time consuming...
Is the kernel produced for RVR correct?
I have an X training vector passed in that is of shape (2,2219), but the RVR fit() function calls RegressionARD's fit() using a kernel K that is of shape (7,7). This results in my coefficients (coef_) being of size 7, which doesn't seem correct since my n_features is 2219.
is there an error in the get_kernel function?
Thanks for the great package!
Not really an "issue", but just wanted to thank you for posting such a nicely done package. I am working on implementing MICE for Python and these models are very helpful.
Regularised bias term in Bayesian Logistic Regression
Grouped ARD Linear/Logit regression
Hi, have you thought about implementing ARD for grouped problem?
verbose
I am not sure, but verbose works wrong:
from skbayes.rvm_ard_models import RVR
rvm = RVR(kernel = 'rbf', verbose=True, n_iter=300)
rvm.fit(X, y)
output:
Iteration: 0, number of features in the model: 2
Iteration: 1, number of features in the model: 3
Iteration: 2, number of features in the model: 4
Iteration: 3, number of features in the model: 5
Iteration: 4, number of features in the model: 6
Iteration: 5, number of features in the model: 7
Iteration: 6, number of features in the model: 8
Iteration: 7, number of features in the model: 9
Iteration: 8, number of features in the model: 10
Iteration: 9, number of features in the model: 11
Iteration: 10, number of features in the model: 12
Iteration: 11, number of features in the model: 13
Iteration: 12, number of features in the model: 14
Iteration: 13, number of features in the model: 15
Iteration: 14, number of features in the model: 16
Iteration: 15, number of features in the model: 17
Iteration: 16, number of features in the model: 18
Iteration: 17, number of features in the model: 19
Iteration: 18, number of features in the model: 20
Iteration: 19, number of features in the model: 21
Iteration: 20, number of features in the model: 22
Iteration: 21, number of features in the model: 23
Iteration: 22, number of features in the model: 24
Iteration: 23, number of features in the model: 25
Iteration: 24, number of features in the model: 26
Iteration: 25, number of features in the model: 27
Iteration: 26, number of features in the model: 28
Iteration: 27, number of features in the model: 29
Iteration: 28, number of features in the model: 30
Iteration: 29, number of features in the model: 31
Iteration: 30, number of features in the model: 32
Iteration: 31, number of features in the model: 33
Iteration: 32, number of features in the model: 34
Iteration: 33, number of features in the model: 35
Iteration: 34, number of features in the model: 36
Iteration: 35, number of features in the model: 37
Iteration: 36, number of features in the model: 38
Iteration: 37, number of features in the model: 39
Iteration: 38, number of features in the model: 40
Iteration: 39, number of features in the model: 41
Iteration: 40, number of features in the model: 42
Iteration: 41, number of features in the model: 43
Iteration: 42, number of features in the model: 44
Iteration: 43, number of features in the model: 45
Iteration: 44, number of features in the model: 46
Iteration: 45, number of features in the model: 47
Iteration: 46, number of features in the model: 48
Iteration: 47, number of features in the model: 49
Iteration: 48, number of features in the model: 50
Iteration: 49, number of features in the model: 51
Iteration: 50, number of features in the model: 52
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Typo in VBLogisticRegression model
Hi there,
thank you for sharing your implementations! In the update of the variational distribution q(alpha) for the variational Bayesian logistic regression model, I believe there is a small mistake.
According to Eq. 10.179 in Bishop's book, we use the expectation of w^T w, and that is mu_N^T mu_N + trace(Sigma_N).
Therefore
(np.sum(w ** 2) + np.sum(Ri ** 2))should be changed to
(np.sum(w ** 2) + np.trace(Ri ** 2))and analogously in the line above.
Hope this helps!
Posterior distribution in Relevance Vector Classifier
Improve performance by using (and then reusing) Cholesky decomposition instead of pinvh
RuntimeWarning: divide by zero encountered in divide
Hi
I met the following warning when I was tuning parameters for RVR.
fast_rvm.py:48: RuntimeWarning: divide by zero encountered in divide
deltaL[recompute] = Qrec2 / (Srec + 1. / delta_alpha) - np.log(1 + Srec*delta_alpha)**
What is the potential reason for this warning?
Replicated Softmax does not work well on documents with different length
Sampling from weights posterior for linear models
I was wondering if there is a clean way to sample from the posterior of weights for linear models. Specifically, I think EBLogisticRegression does not return the posterior covariance. Is that correct? I was wondering if there is a reason for that.
Installation with python3.8 returns error: PyThreadState
I am executing `` but I am getting the following errors. Thus, I have tried python setup.py build_ext -i from this link but I am still getting the same errors.
skbayes/hidden_markov_models/hmm.c:28348:21: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_type’; did you mean ‘curexc_type’?
28348 | *type = tstate->exc_type;
| ^~~~~~~~
| curexc_type
skbayes/hidden_markov_models/hmm.c:28349:22: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_value’; did you mean ‘curexc_value’?
28349 | *value = tstate->exc_value;
| ^~~~~~~~~
| curexc_value
skbayes/hidden_markov_models/hmm.c:28350:19: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_traceback’; did you mean ‘curexc_traceback’?
28350 | *tb = tstate->exc_traceback;
| ^~~~~~~~~~~~~
| curexc_traceback
skbayes/hidden_markov_models/hmm.c: In function ‘__Pyx__ExceptionReset’:
skbayes/hidden_markov_models/hmm.c:28357:24: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_type’; did you mean ‘curexc_type’?
28357 | tmp_type = tstate->exc_type;
| ^~~~~~~~
| curexc_type
skbayes/hidden_markov_models/hmm.c:28358:25: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_value’; did you mean ‘curexc_value’?
28358 | tmp_value = tstate->exc_value;
| ^~~~~~~~~
| curexc_value
skbayes/hidden_markov_models/hmm.c:28359:22: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_traceback’; did you mean ‘curexc_traceback’?
28359 | tmp_tb = tstate->exc_traceback;
| ^~~~~~~~~~~~~
| curexc_traceback
skbayes/hidden_markov_models/hmm.c:28360:13: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_type’; did you mean ‘curexc_type’?
28360 | tstate->exc_type = type;
| ^~~~~~~~
| curexc_type
skbayes/hidden_markov_models/hmm.c:28361:13: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_value’; did you mean ‘curexc_value’?
28361 | tstate->exc_value = value;
| ^~~~~~~~~
| curexc_value
skbayes/hidden_markov_models/hmm.c:28362:13: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_traceback’; did you mean ‘curexc_traceback’?
28362 | tstate->exc_traceback = tb;
| ^~~~~~~~~~~~~
| curexc_traceback
skbayes/hidden_markov_models/hmm.c: In function ‘__Pyx__GetException’:
skbayes/hidden_markov_models/hmm.c:28407:24: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_type’; did you mean ‘curexc_type’?
28407 | tmp_type = tstate->exc_type;
| ^~~~~~~~
| curexc_type
skbayes/hidden_markov_models/hmm.c:28408:25: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_value’; did you mean ‘curexc_value’?
28408 | tmp_value = tstate->exc_value;
| ^~~~~~~~~
| curexc_value
skbayes/hidden_markov_models/hmm.c:28409:22: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_traceback’; did you mean ‘curexc_traceback’?
28409 | tmp_tb = tstate->exc_traceback;
| ^~~~~~~~~~~~~
| curexc_traceback
skbayes/hidden_markov_models/hmm.c:28410:13: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_type’; did you mean ‘curexc_type’?
28410 | tstate->exc_type = local_type;
| ^~~~~~~~
| curexc_type
skbayes/hidden_markov_models/hmm.c:28411:13: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_value’; did you mean ‘curexc_value’?
28411 | tstate->exc_value = local_value;
| ^~~~~~~~~
| curexc_value
skbayes/hidden_markov_models/hmm.c:28412:13: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_traceback’; did you mean ‘curexc_traceback’?
28412 | tstate->exc_traceback = local_tb;
| ^~~~~~~~~~~~~
| curexc_traceback
skbayes/hidden_markov_models/hmm.c: In function ‘__Pyx__ExceptionSwap’:
skbayes/hidden_markov_models/hmm.c:30306:24: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_type’; did you mean ‘curexc_type’?
30306 | tmp_type = tstate->exc_type;
| ^~~~~~~~
| curexc_type
skbayes/hidden_markov_models/hmm.c:30307:25: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_value’; did you mean ‘curexc_value’?
30307 | tmp_value = tstate->exc_value;
| ^~~~~~~~~
| curexc_value
skbayes/hidden_markov_models/hmm.c:30308:22: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_traceback’; did you mean ‘curexc_traceback’?
30308 | tmp_tb = tstate->exc_traceback;
| ^~~~~~~~~~~~~
| curexc_traceback
skbayes/hidden_markov_models/hmm.c:30309:13: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_type’; did you mean ‘curexc_type’?
30309 | tstate->exc_type = *type;
| ^~~~~~~~
| curexc_type
skbayes/hidden_markov_models/hmm.c:30310:13: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_value’; did you mean ‘curexc_value’?
30310 | tstate->exc_value = *value;
| ^~~~~~~~~
| curexc_value
skbayes/hidden_markov_models/hmm.c:30311:13: error: ‘PyThreadState’ {aka ‘struct _ts’} has no member named ‘exc_traceback’; did you mean ‘curexc_traceback’?
30311 | tstate->exc_traceback = *tb;
| ^~~~~~~~~~~~~
| curexc_traceback
Bug in RVC
So I've been experimenting with you code for a project I am working with. Great work on the implementation. It is much appreciated that you have taken the time to make this.
I might be using it wrong, but I think I found a bug in your code. Take a look at the following simple example:
>>> import skbayes.rvm_ard_models
>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>>
>>> rvm = skbayes.rvm_ard_models.RVC()
>>> rvm.fit([[-1], [1]], [0, 1])
RVC(coef0=1, degree=2, fit_intercept=True, gamma=None, kernel='rbf',
kernel_params=None, n_iter=300, n_iter_solver=30, solver='lbfgs_b',
tol=0.0001, tol_solver=1e-05, verbose=False)
>>>
>>> x = np.linspace(-5, 5, 200).reshape(200, 1)
>>> y = rvm.predict_proba(x)[:,0]
>>> plt.plot(y)
>>> plt.savefig("out.pdf")The figure produced:
out.pdf
It looks like the aposteriori estimate only includes the [1] and not the [-1].
shape of coef_ attribute
I've been using the RVC model for binary classification and the shape of the coef_ and the active_ attribute after fitting is (1,n_samples) and not (n_features) what I had expected. What does the coef_ attribute represent here?
Broken links in README
It's hard to navigate from the titlepage
error for installation on Windows computer with python 3 and anaconda
copying skbayes\rvm_ard_models_init_.py -> build\lib.win-amd64-3.5\skbaye
s\rvm_ard_models
running build_ext
No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying f
rom distutils
building 'skbayes.decomposition_models.gibbs_lda_cython' extension
creating build\temp.win-amd64-3.5
creating build\temp.win-amd64-3.5\Release
creating build\temp.win-amd64-3.5\Release\skbayes
creating build\temp.win-amd64-3.5\Release\skbayes\decomposition_models
cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -Ic:\anaconda3\lib\site-packag
es\numpy\core\include -Ic:\anaconda3\include -Ic:\anaconda3\include /Tcskbaye
s/decomposition_models/gibbs_lda_cython.c /Fobuild\temp.win-amd64-3.5\Release\sk
bayes/decomposition_models/gibbs_lda_cython.obj -O3
Could not locate executable cl.exe
Executable cl.exe does not exist
error: Command "cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -Ic:\anaconda3\
lib\site-packages\numpy\core\include -Ic:\anaconda3\include -Ic:\anaconda3\i
nclude /Tcskbayes/decomposition_models/gibbs_lda_cython.c /Fobuild\temp.win-amd6
4-3.5\Release\skbayes/decomposition_models/gibbs_lda_cython.obj -O3" failed with
exit status 1
Loading the package
Hi,
I've not really been able to use the package yet. I have tried installing it using the pip installer, which did not work.
Instead, I have cloned the package and tried to do python setup.py install, which worked, but the code examples don't seem to work.
I realised that I have to probably import sklearn_bayes, but when I dir it, it contains nothing beyond:
['all',
'builtins',
'doc',
'file',
'name',
'package',
'path',
'version']
Am I doing something wrong?
Fast analytic inversion of precision matrix
This should speed up evidence maximization procedure for RVM
Issues with near-singular data - ridge as solution?
Hello,
When fitting BayesianRegression with this data:
X = np.array([[ 0.1, -0.1, -0.2, 0.02],
[ 0.3, -0.3, -0.6, 0.06],
[ 0.4, -0.4, -0.8, 0.08],
[ 0.5, -0.5, -1., 0.1 ]])
Y = np.array([ 0.2, 0.6, 0.8, 1. ])
The returned parameters are pretty crazy:
Out[16]:
{'bias_term': 0.65000000000000002,
'precision': array([[ 8.15645225e+31, -8.15645225e+31, -1.63129045e+32,
1.63129045e+31],
[ -8.15645225e+31, 8.15645225e+31, 1.63129045e+32,
-1.63129045e+31],
[ -1.63129045e+32, 1.63129045e+32, 3.26258090e+32,
-3.26258090e+31],
[ 1.63129045e+31, -1.63129045e+31, -3.26258090e+31,
3.26258090e+30]]),
'weights': array([ 0.18599761, -0.34392501, -0.68785002, 0.47188674])}
The issue is that X is nearly singular. Using ridge regression can help in such cases - would it make sense to add a scaled identity to the covariance/precision somewhere along the line to deal with cases like this?
Is there any method to sample from bernoulli mixture model?
'BayesianLogisticRegression' object has no attribute '_mask_val'
Hi,
Is this a known issue?
Cant even run fit ....
blr=BayesianLogisticRegression(n_iter=300, tol=1e-5, fit_intercept=False, verbose=True)
clf.fit(X_train, y_train)
File "/Library/Python/2.7/site-packages/skbayes/linear_models/bayes_logistic.py", line 87, in fit
y_bin[~mask] = self._mask_val
AttributeError: 'BayesianLogisticRegression' object has no attribute '_mask_val'
Is there any documentation?
This looks really awesome and would love to get started with this. Is there an official docs page?
pip install failed: ValueError: Unknown MS Compiler version 1900
I have failed to install the package, and the error is as follows:
......
File "c:\program files\anaconda3\lib\distutils\cygwinccompiler.py", line 86, in get_msvcr
raise ValueError("Unknown MS Compiler version %s " % msc_ver)
ValueError: Unknown MS Compiler version 1900
----------------------------------------
Command ""c:\program files\anaconda3\python.exe" -u -c "import setuptools, tokenize;file='C:\Users\yzzha\AppData\Local\Temp\pip-y2f74zoi-build\setup.py';f=getattr(tokenize, 'open', open)(file);code=f.read().replace('\r\n', '\n');f.close();exec(compile(code, file, 'exec'))" install --record C:\Users\yzzha\AppData\Local\Temp\pip-sejc_xfs-record\install-record.txt --single-version-externally-managed --compile" failed with error code 1 in C:\Users\yzzha\AppData\Local\Temp\pip-y2f74zoi-build\
Can anyone tell me how to fix it?
Thanks.
What's the license?
I'd like to ask Kaggle to include this in their Python Docker image, but I can't figure out what the license is...
Thanks, Chad
Please apply a licence to the project
Please apply a licence to the project so that others can legally make use of it and are aware of their rights.
pinvh deprecated in scikit-learn 0.19 removed in 0.21
utils.extmath.pinvh was deprecated in scikit-learn version 0.19 and removed in version 0.21. The following error therefore occurs when using scikit-lean >= 0.21:
~\AppData\Local\Continuum\anaconda3\envs\chemo2\lib\site-packages\skbayes\rvm_ard_models\fast_rvm.py in <module>
5 from sklearn.utils import check_X_y,check_array,as_float_array
6 from sklearn.utils.multiclass import check_classification_targets
----> 7 from sklearn.utils.extmath import pinvh,log_logistic,safe_sparse_dot
8 from sklearn.metrics.pairwise import pairwise_kernels
9 from sklearn.utils.validation import check_is_fitted
ImportError: cannot import name 'pinvh'
VBGMMARD vs VBGMM in scikit-learn
Is there any between VBGMMARD class in sklearn_bayes and VBGMM in sklearn ?
Installation python3.7 fails
Building wheel for skbayes (setup.py) ... error
ERROR: Command errored out with exit status 1:
command: 'c:\users\xxxxx\appdata\local\programs\python\python37\python.exe' -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\Users\xxxx\AppData\Local\Temp\pip-req-build-tkvmaq7f\setup.py'"'"'; file='"'"'C:\Users\xxxx\AppData\Local\Temp\pip-req-build-tkvmaq7f\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(file);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, file, '"'"'exec'"'"'))' bdist_wheel -d 'C:\Users\xxxx\AppData\Local\Temp\pip-wheel-a5gqn_p3'
cwd: C:\Users\xxxx\AppData\Local\Temp\pip-req-build-tkvmaq7f\
predict_proba generating predictions > number of classes
I'm training my classifier using
clf = RVC(kernel = 'rbf')
clf.fit(embeddings, labelsNum)
were the number of labels = 10
When I inspect the clf I get this:
with open('RVC.pkl', 'r') as rvc:
le_rvc, clf_rvc = pickle.load(rvc)
array(['Ariel_Sharon', 'Colin_Powell', 'Donald_Rumsfeld', 'George_W_Bush',
'Gerhard_Schroeder', 'Hugo_Chavez', 'Jean_Chretien',
'John_Ashcroft', 'Junichiro_Koizumi', 'Tony_Blair'],
dtype='|S17')
Which is correct, 10 classes.
However, when I try to predict my test set by running this
predictions = clf.predict_proba(rep).ravel()
maxI = np.argmax(predictions)
person = le.inverse_transform(maxI)
confidence = predictions[maxI]
the length of predictions is 20
Meaning that when
le.inverse_transform(maxI)
is called it fails if maxl is >10
I must be doing something wrong on my side, but is there a reason why the clf is predicting more values than needed?
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