GithubHelp home page GithubHelp logo

t5i0m7 / online_psp_matlab Goto Github PK

View Code? Open in Web Editor NEW

This project forked from flatironinstitute/online_psp_matlab

0.0 0.0 0.0 53.24 MB

Benchmark of online PCA algorithms

License: GNU General Public License v2.0

MATLAB 100.00%

online_psp_matlab's Introduction

Online-PSP

Efficient MATLAB implementation of online Principal Subspace Projection algorithms (Fast Similarity Matching[1], Incremental PCA[2,3], and Candid Covariance Incremental PCA[2,4])

For the more complete Python version please go to the link online-psp

Installation

Clone the repository or unzip the source and add recursively folders from the src folder to the MATLAB path

EXAMPLES

Basic Example

k -> subspace dimension
d -> number of features
% we suggest to standardize data using the standardize_data function
[X,~,~] = standardize_data(X,0,0);

fsm = FSM(k, d, [], [], [], []);
for i = 1:n    
    fsm.fit_next(x(:,i)');
end

components = fsm.get_components([]);

Detailed Example

For more detailed examples explore the demo_XXX.m files

References

[1] Pehlevan, Cengiz, Anirvan M. Sengupta, and Dmitri B. Chklovskii. "Why do similarity matching objectives lead to Hebbian/anti-Hebbian networks?." Neural computation 30, no. 1 (2018): 84-124.

[2] Cardot, Hervé, and David Degras. "Online Principal Component Analysis in High Dimension: Which Algorithm to Choose?." arXiv preprint arXiv:1511.03688 (2015).

[3] Arora, R., Cotter, A., Livescu, K. and Srebro, N., 2012, October. Stochastic optimization for PCA and PLS. In Communication, Control, and Computing (Allerton), 2012 50th Annual Allerton Conference on (pp. 861-868). IEEE.

[4] Weng, J., Zhang, Y. and Hwang, W.S., 2003. Candid covariance-free incremental principal component analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(8), pp.1034-1040.

License

This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.

online_psp_matlab's People

Contributors

agiovann avatar victorminden avatar cpehlevan avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.