LIBTwinSVM

Contents

1. Core Features
2. Installation Guide
3. Quick Start
4. Documentation
5. License

Core Features

LIBTwinSVM is an easy-to-use implementation of Twin Support Vector Machine. It is licensed under the terms of GNU GPL v3. This application comes with a user interface which makes using the algorithm so handy for Data Scientists, Machine Learning Researchers and whoever else that is interested in Machine Learning.

• A simple and user-friendly Graphical User Interface (GUI).
• Supports both standard TwinSVM and Least Squares TwinSVM classifiers.
• Easy to import data in CSV & LIBSVM format.
• A dataset can be loaded with shuffling and normalization.
• A fast optimizer (clipDCD) is improved and implemented in C++ to solve optimization problems of TwinSVMs.
• Supports Linear, RBF and Rectangular kernel.
• Supports Binary and Multi-class classification (One-vs-All & One-vs-One).
• The OVA and OVO estimators are compatible with scikit-learn tools such as GridSearchCV, cross_val_score, etc.
• A classifier can be evaluated using either K-fold cross-validation or Training/Test split.
• Supports grid search over estimators' hyper-parameters.
• The detailed classification results can be saved in an Excel-format spreadsheet file.
• The classification results can be logged during the grid search process to not lose results in case of power failure.
• A feature-rich visualization tool to show decision boundaries and geometrical interpretation of TwinSVMs.
• The best-fitted classifier can be saved on the disk after the grid search process.
• The pre-trained models can be loaded and evaluated on the test samples.

Installation Guide

Dependencies

LIBTwinSVM depends on the following packages.

Quick Installation

For Installing LIBTwinSVM you can choose one of the following commands based on your Operating System and your Python version. Please note that for installing the latest bugfixes and features, we recommend you to install the library from the source.

• Linux & Mac OS:

pip3 install libtwinsvm

• Windows:

pip install libtwinsvm

Installation from the source

1. Downloading LIBTWinSVM

First, make sure that Git is installed as it is required for getting the source code. Then open Git in any arbitrary path and enter the following command:

git clone --recursive https://github.com/mir-am/LIBTwinSVM

2. Downloading Requirements

Before installing any packages, we recommend you to upgrade pip:

• Linux & Mac OS:

pip3 install -U pip

• Windows:

pip install -U pip

For LIBTwinSVM installation, Numpy and Cython must be installed. You can install them by entering the following commands in your terminal. If you already have Cython and Numpy installed, you can skip to the next section.

• Linux & Mac OS: For installing Numpy & Cython on your computer, you should enter the following command in the terminal.

pip3 install numpy cython

• Windows: for installing the requirements on windows, you should enter the following command in the command prompt.

pip install numpy cython

3. Installing LIBTwinSVM

Go to LIBTwinSVM folder where you have downloaded the source code in step 2. Then enter the following command in the terminal:

• Linux & Mac OS:

pip3 install .

• Windows:

pip install .

Quick start

After LIBTwinSVM was installed, for running the GUI application, open the terminal and enter the following code:

• Linux & Mac OS:

python3 -m libtsvm

• Windows:

python -m libtsvm


## Uninstall LIBTwinSVM

For uninstalling LIBTwinSVM enter the following command in the terminal:

* Linux & Mac OS:
```python
pip3 uninstall libtsvm

• Windows:

pip uninstall libtsvm

Documentation

Usage examples and API reference can be found on the project's Read the Docs page.

License

LIBTwinSVM library is licensed under the terms of GNU General Public License v3. This library can be used for both academic and commercial purposes. For more information, check out the LICENSE file.