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MLDemos Graphical User Interface Different visualizations and parameter effects Visualizations of sample plots, densities and correlations
SVM+RBF classification Sparse Gaussian Process Regression Dynamical Systems (SEDS) with Obstacle Avoidance
Kernel PCA Isolines Reward Maximization with Genetic Algorithms
Support Vector Regression with RBF kernel Relevance Vector Machine classification with RBF kernel Boosting with Random Circles Weak Learners
Multi-Class SVM with RBF kernel Clustering with Gaussian Mixture Models Growing Hierarchical Self Organizing Maps