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kakuremino avatar kei500 avatar steveltn avatar wvengen avatar

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liblinear-ruby's Issues

Possible to save model to db storage?

Hey,

I'm looking to write some production code using liblinear in a Ruby on Rails application. I took a look at save_model, and it looks feasible to store the output in a db text column. Ideally I'd like to get an in memory string representation of the trained model (instead of writing to file, then reading) and load from in memory string as well

Unfortunately I'm not too familiar with ruby wrapper code. I'm assuming there has to be some additional interface to get all the attributes the model has.

How much work do you think it would take to add that feature?

Quiet mode

Thanks for the gem!
I'm looking how to silence the (training) output. There is something like Liblinearswig.set_print_string_function but I don't really know how to use it.

RubyML list

Dear @kei500 ,

we've recently added liblinear-ruby to our Awesome RubyML list: https://github.com/arbox/machine-learning-with-ruby

Ruby bindings for LIBLINEAR are really important for the Ruby ML ecosystem. So we introduced the rubyml topic which connects all ML related projects written in and for Ruby.

Please consider adding the rubyml topic to your repository :)

Thank you!

Error using gem on Windows

I have liblinear installed and accessible via the path. SWIG.exe is also accessible via the path.

I installed the gem via gem install 'liblinear-ruby' and did not have any errors.

Then in my file, I have require 'liblinear'

This resulted in the following error message:
2.2.0/rubygems/core_ext/kernel_require.rb:54:in require': 193: %1 is not a valid Win32 application. - C:/RailsInstaller/Ruby2.2.0/lib/ruby/gems/2.2.0/extensions/x86-mingw32/2.2.0/liblinear-ruby-1.0.2/liblinearswig.so (LoadError)`

I did verify that liblinearswig.so existed in the directory listed. It seems to fail to find the require 'liblinearswig' in C:\RailsInstaller\Ruby2.2.0\lib\ruby\gems\2.2.0\gems\liblinear-ruby-1.0.2\lib\liblinear.rb

Any help would be appreciated

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