ThunderSVM Ruby

ThunderSVM - high performance parallel SVMs - for Ruby

🔥 Uses GPUs and multi-core CPUs for blazing performance

For a great intro on support vector machines, check out this video.

Installation

Add this line to your application’s Gemfile:

gem"thundersvm"

On Mac, also install OpenMP:

brew install libomp

Getting Started

Prep your data

x=[[1,2],[3,4],[5,6],[7,8]]y=[1,2,3,4]

Train a model

model=ThunderSVM::Regressor.newmodel.fit(x,y)

Use ThunderSVM::Classifier for classification and ThunderSVM::Model for other models

Make predictions

model.predict(x)

Save the model to a file

model.save_model("model.txt")

Load the model from a file

model=ThunderSVM.load_model("model.txt")

Get support vectors

model.support_vectors

Cross-Validation

Perform cross-validation

model.cv(x,y)

Specify the number of folds

model.cv(x,y,folds: 5)

Parameters

Defaults shown below

ThunderSVM::Model.new(svm_type: :c_svc,# type of SVM (c_svc, nu_svc, one_class, epsilon_svr, nu_svr)kernel: :rbf,# type of kernel function (linear, polynomial, rbf, sigmoid)degree: 3,# degree in kernel functiongamma: nil,# gamma in kernel functioncoef0: 0,# coef0 in kernel functionc: 1,# parameter C of C-SVC, epsilon-SVR, and nu-SVRnu: 0.5,# parameter nu of nu-SVC, one-class SVM, and nu-SVRepsilon: 0.1,# epsilon in loss function of epsilon-SVRmax_memory: 8192,# constrain the maximum memory size (MB) that thundersvm usestolerance: 0.001,# tolerance of termination criterionprobability: false,# whether to train a SVC or SVR model for probability estimatesgpu: 0,# specify which gpu to usecores: nil,# number of cpu cores to use (defaults to all)verbose: false# verbose mode)

Data

Data can be a Ruby array

[[1,2],[3,4],[5,6],[7,8]]

Or a Numo array

Numo::DFloat.cast([[1,2],[3,4],[5,6],[7,8]])

Or the path a file in libsvm format (better for sparse data)

model.fit("train.txt")model.predict("test.txt")

GPUs

To run ThunderSVM on GPUs, you’ll need to build the library from source.

Linux

git clone --recursive --branch v0.3.4 https://github.com/Xtra-Computing/thundersvm
cd thundersvm
mkdir build
cd build
cmake ..
make

Specify the path to the shared library with:

ThunderSVM.ffi_lib="path/to/build/lib/libthundersvm.so"

Windows

Follow the official instructions. Specify the path to the shared library with:

ThunderSVM.ffi_lib="path/to/build/lib/libthundersvm.dll"

Resources

• ThunderSVM: A Fast SVM Library on GPUs and CPUs
• A Practical Guide to Support Vector Classification

History

View the changelog

Contributing

Everyone is encouraged to help improve this project. Here are a few ways you can help:

• Report bugs
• Fix bugs and submit pull requests
• Write, clarify, or fix documentation
• Suggest or add new features

To get started with development:

git clone https://github.com/ankane/thundersvm-ruby.git
cd thundersvm-ruby
bundle install
bundle exec rake test