Hi everyone, I'm trying to figure out the best way to proceed. Here are some things I noticed.
1) scikit's libsvm checkin is currently version 300. The last release was in April and the version is 312. Are there plans to use the newer version? The svm_node struct changed, so it's not as trivial as dropping in the files. 2) libsvm comes with a ctypes binding. What if scikit contributed a cython binding that was in the libsvm project? Then scikit could just use the libsvm cython module for implementing fit(), predict(), etc. 3) Where is the test suite in the libsvm project itself? Perhaps they have something that's not in the main download? The scikit test suite looks pretty good, but I've gotten used to making a library and then running the builtin test suite. 4) I opened another issue on my github of some compiler warnings from the clang++ compiler. It turns out that there are a lot of calls to malloc where the return pointer is unchecked. So basically the library can crash at any time. Someone already offered to make a nontrivial patch using std::vector and new to fix it. How do we want to proceed? What's the strategy to merge the change with libsvm and the scikit project? https://github.com/erg/libsvm/issues/1 Even if we got a cython module into the libsvm project and just called libsvm as a python module, there would still be the problem of merging feature enhancements and bugfixes. Thoughts? Doug On Thu, Sep 27, 2012 at 9:44 AM, Mathieu Blondel <[email protected]> wrote: > Some parts which are not relevant for inclusion in scikit-learn have also > been removed (command line, libsvm file parsing, ...). > > Since our copy of libsvm is quite heavily patched already (dense data, > sample weight, label order, ...), I wonder if it wouldn't be easier to > maintain our own libsvm copy directly in scikit-learn (which is basically > what we are currently doing already). > > Mathieu > > ------------------------------------------------------------------------------ > Everyone hates slow websites. So do we. > Make your web apps faster with AppDynamics > Download AppDynamics Lite for free today: > http://ad.doubleclick.net/clk;258768047;13503038;j? > http://info.appdynamics.com/FreeJavaPerformanceDownload.html > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > ------------------------------------------------------------------------------ Everyone hates slow websites. So do we. Make your web apps faster with AppDynamics Download AppDynamics Lite for free today: http://ad.doubleclick.net/clk;258768047;13503038;j? http://info.appdynamics.com/FreeJavaPerformanceDownload.html _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
