FSA

A fast feature selection method described in the paper: A. Barbu, Y. She, L. Ding, G. Gramajo. Feature Selection with Annealing for Computer Vision and Big Data Learning. IEEE PAMI, 39, No. 2, 272–286, 2017 https://arxiv.org/abs/1310.2880

GETTING STARTED

A simple version implemented in pyTorch is available in the /Python directory.

For the heavy-duty version implemented in C++ you need the following:

-HARDWARE

• COMPUTER WITH WINDOWS OR LINUX

-SOFTWARE

• CMAKE (VERSION 3.02 OR UP)
• PYTHON (VERSION 2.7 OR UP)
• NUMPY (INSTALLED INTO PYTHON)
• A C++ COMPILER THAT SUPPORTS C++11 OR C++0X
• Install Git

TO OBTAIN A COPY OF OUR SOFTWARE, FOLLOW THE FOLLOWING INSTRUCTIONS.

You can either download FSA by opening navigating to the top right corner and clicking "Clone or Download" or running

• git clone https://github.com/barbua/FSA.git

INSTALLING OUR SOFTWARE

Once you've obtained a copy of the software by hitting "Clone or Download" it will come as FSA.zip. Unzip this file however you can and navigate into the unzipped folder named FSA. Otherwise, if you have cloned the repository using git clone https://github.com/barbua/FSA.git you can go right into the FSA folder.

The folder hierarchy should look like this when you enter FSA Folder
-bin (folder)
-include (folder)
-src (folder)
CMakeLists.txt (file)
.
.(additional files)

WINDOWS

Enter the bin folder in your FSA folder It should be empty wiith the exception of a StartHere.txt file.

Run the following commands depending on the Command line interface you are using.
Command prompt: cmake ..
Power Shell: cmake ..
Git Bash: cmake ../

This will generate solution files if you are using Visual Studios as your generator (To learn more about generators https://cmake.org/cmake/help/v3.0/manual/cmake-generators.7.html)

If you have an .sln file in the bin directory go ahead and click on it and open it up with Visual Studios. There you will hit Build which will create the dynamic library in your bin directory!

LINUX

Enter the bin folder in your FSA folder It should be empty with the exception of a StartHere.txt file.

Run the following commands cmake ../ make

This will generate either a libPyFSA.a, libPyFSA.so. You can link to this in order to use our code. Use Header files to figure out how to use our API.

Using and Testing Code

After a successful build, you can use the code in three different ways! You can implement the code in Octave/Matlab, import the module and use the function with python inputs in Python, or simply make a client program to employ the public methods in the PyFSA header file! You can also use this function in C as the API functions available to clients has been declared extern "C".