Natural Computation Methods for Machine Learning Note 15 In this article, we talk about Particle Swarm Optimization. In last post, we talked Computational tools, including Cellular automata Ant Colony Optimization Particle Swarm Optimization Particle Swarm Opt…

Natural Computation Methods for Machine Learning Note 14 Swarm Intelligence Intelligence <- Social behavior Intelligence can emerge from social interaction. Emergent behaviour – when a group behaves in ways that were not ”programmed” into its members Swarm …

Natural Computation Methods for Machine Learning Note 13 Properties of EC EC is parallel search (many balls in the landscape). Want to prevent all individuals from converging to the same solution (premature convergence – a common problem) The task of mutation …

Natural Computation Methods for Machine Learning Note 12 From course, I learned Evolutional Computing. Evolutionary computing (EC) population method Used for problems where the task is to maximize some measure of success Same family of problems as in RL, but v…

Natural Computation Methods for Machine Learning Note 11 Let us firstly revisit completive learning and SOFM Review CL and SOFM A node position (in the input space) is its weight vector, i.e. nodes move around in the same space as the data. Purpose of unsuperv…

Natural Computation Methods for Machine Learning Note 10 In this note, we are going talk about Deep Learning very briefly. Radial Basis Function Networks RBFNs are feedforward networks, where: The hidden nodes (the RBF nodes) compute distances, instead of weig…

Unsupervised Learning To learn from unlabeled data (only inputs, no target information). Most often for classification. Requires that class membership can be detected by structural properties (features) in the data, and that the learning system can be fund the…

Natural Computation Methods for Machine Learning Note 07 From today, we are going to introduce reinforcement learning(RL). Forget ANNs for a while - RL is a field in its own right, independent from ANNs. However, as we will see, ANNs are sometimes used in RL. …

Natural Computation Methods for Machine Learning Note 06 In this course, we learn more on extensions. and prior knowledge. Automatic dimensioning We want to minimize the number of hidden nodes(=> less overfitting) The approaches: start with a large networks an…

Natural Computation Methods for Machine Learning Note 05 Let's continue talk about overtraining. Training set size The number of training set samples should be much larger than the number of weights roughly for ​ \(N^2\)(N = the number of weights). What to do …