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Source Code

    git repository

Implemented Methods

Classification
  • Support Vector Machine (SVM) (C, nu, Pegasos)
  • Relevance Vector Machine (RVM)
  • Gaussian Mixture Models (GMM)
  • Multi-Layer Perceptron + BackPropagation
  • Gentle AdaBoost + Naive Bayes
  • Approximate K-Nearest Neighbors (KNN)
  • Gaussian Process Classification (GP)
  • Random Forests
Regression
  • Support Vector Regression (SVR)
  • Relevance Vector Regression (RVR)
  • Gaussian Mixture Regression (GMR)
  • MLP + BackProp
  • Approximate KNN
  • Gaussian Process Regression (GPR)
  • Sparse Optimized Gaussian Processes (SOGP)
  • Locally Weighed Scatterplot Smoothing (LOWESS)
  • Locally Weighed Projection Regression (LWPR)
Dynamical Systems
  • GMM+GMR
  • LWPR
  • SVR
  • SEDS
  • SOGP (Slow!)
  • MLP
  • KNN
  • Augmented-SVM (ASVM)
Clustering
  • K-Means
  • Soft K-Means
  • Kernel K-Means
  • K-Means++
  • GMM
  • One Class SVM
  • FLAME
  • DBSCAN
Projections
  • Principal Component Analysis (PCA)
  • Kernel PCA
  • Independent Component Analysis (ICA)
  • Canonical Correlation Analysis (CCA)
  • Linear Discriminant Analysis (LDA)
  • Fisher Linear Discriminant
  • EigenFaces to 2D (using PCA)
Reward Maximization (Reinforcement Learning)
  • Random Search
  • Random Walk
  • PoWER
  • Genetic Algorithms (GA)
  • Particle Swarm Optimization
  • Particle Filters
  • Donut
  • Gradient-Free Methods (nlopt)

Contributing

If you are developing a new algorithm that could fit into the MLDemos framework and would like to see it integrated into the software, please get in contact (see info below) and describe what type of help you require for the implementation of a MLDemos plugin.

Acknowledgements

This program would not exist if a number of people had not put a lot of effort into implementing the different algorithms that are combined here into a single program.
  • Florent D'Hallouin (GMM + GMR) - LASA
  • Dan Grollman (SOGP) - LASA
  • Mohammad Khansari (SEDS + DSAvoid) - LASA
  • Ashwini Shukla (ASVM, ARD Kernels) - LASA
  • Stephane Magnenat (ESMLR) - website
  • Chih-Chung Chang and Chih-Jen Lin (libSVM) - website
  • David Mount and Sunik Arya (ANN library) - website
  • Davis E. King (DLIB) - website
  • Stefan Klanke and Sethu Vijayakumar (LWPR) - website
  • Robert Davies (Newmat) - website
  • JF Cardoso (ICA) - website
  • Steven G. Johnson (NLOpt) - website
  • The WillowGarage crowd (OpenCV) - website
  • Trolltech/Nokia/Digia (Qt) - website
  • The authors of several of the icons - website
  • The PhD students following the 2012 ML class at EPFL (Julien Eberle, Pierre-Antoine Sondag, Guillaume deChambrier, Klas Kronander, Renaud Richardet, Raphael Ullman)

Moreover, the program itself would be far less performant without the work of the support and development team at LASA: Christophe Paccolat, Nicolas Sommer and Otpal Vittoz.

Thanks also to the people who have not contributed code but have contributed no less directly: Aude Billard, for being one of the best bosses one could wish for, François Fleuret, for a bunch of fruitful discussions, and the AML 2010,  and 2011 classes for patiently giving it a first test-drive.