A collection of machine learning algorithms. More...
Collaboration diagram for Learning Machines:
Classes | |
| class | iCub::learningmachine::DatasetRecorder |
| This 'machine learner' demonstrates how the IMachineLearner interface can be used to easily record samples to a file. More... | |
| class | iCub::learningmachine::DummyLearner |
| This dummy machine learner demonstrates how the IMachineLearner interface can be used in practice. More... | |
| class | iCub::learningmachine::IFixedSizeLearner |
| An generalized interface for a learning machine with a fixed domain and codomain size. More... | |
| class | iCub::learningmachine::IMachineLearner |
| A generalized interface for a learning machine for offline and online learning machines (e.g. More... | |
| class | iCub::learningmachine::LinearGPRLearner |
| Standard linear Bayesian regression or, equivalently, Gaussian Process Regression with a linear covariance function. More... | |
| class | iCub::learningmachine::LSSVMLearner |
| This is basic implementation of the LSSVM algorithms. More... | |
| class | iCub::learningmachine::Prediction |
| A class that represents a prediction result. More... | |
| class | iCub::learningmachine::RLSLearner |
| Recursive Regularized Least Squares (a.k.a. More... | |
Typedefs | |
| typedef PortableT< IMachineLearner > | iCub::learningmachine::MachinePortable |
| A portable wrapper around an IMachineLearner. | |
Detailed Description
A collection of machine learning algorithms.
Typedef Documentation
◆ MachinePortable
A portable wrapper around an IMachineLearner.
Definition at line 39 of file MachinePortable.h.
