Search Java Classes and Packages
#Org.neuroph.nnet.learning Classes and Interfaces - 26 results found.
| Name | Description | Type | Package | Framework |
| AntiHebbianLearning | A variant of Hebbian learning called Anti-Hebbian learning. | Class | org.neuroph.nnet.learning | Neuroph |
| BackPropagation | Back Propagation learning rule for Multi Layer Perceptron neural networks. | Class | org.neuroph.nnet.learning | Neuroph |
| BinaryDeltaRule | Delta rule learning algorithm for perceptrons with step functions. | Class | org.neuroph.nnet.learning | Neuroph |
| BinaryHebbianLearning | Hebbian-like learning algorithm used for Hopfield network. | Class | org.neuroph.nnet.learning | Neuroph |
| Cluster | This class represents a single cluster, with corresponding centroid and assigned vectorsAuthor:Zoran Sevarac | Class | org.neuroph.nnet.learning.kmeans | Neuroph |
| CompetitiveLearning | Competitive learning rule. | Class | org.neuroph.nnet.learning | Neuroph |
| ConvolutionalBackpropagation | Class | org.neuroph.nnet.learning | Neuroph | |
| DynamicBackPropagation | Backpropagation learning rule with dynamic learning rate and momentumAuthor:Zoran Sevarac See Also:Serialized Form | Class | org.neuroph.nnet.learning | Neuroph |
| GeneralizedHebbianLearning | A variant of Hebbian learning called Generalized Hebbian learning. | Class | org.neuroph.nnet.learning | Neuroph |
| HopfieldLearning | Learning algorithm for the Hopfield neural network. | Class | org.neuroph.nnet.learning | Neuroph |
| InstarLearning | Hebbian-like learning rule for Instar network. | Class | org.neuroph.nnet.learning | Neuroph |
| KMeansClustering | 1. | Class | org.neuroph.nnet.learning.kmeans | Neuroph |
| KNearestNeighbour | calculate distances to all vectors from list and find minimum vector | Class | org.neuroph.nnet.learning.knn | Neuroph |
| KohonenLearning | Learning algorithm for Kohonen network. | Class | org.neuroph.nnet.learning | Neuroph |
| KVector | Represents feature vector used in k-means clustering algorithmAuthor:Zoran Sevarac, Uros Stojkic | Class | org.neuroph.nnet.learning.kmeans | Neuroph |
| LMS | LMS learning rule for neural networks. | Class | org.neuroph.nnet.learning | Neuroph |
| MomentumBackpropagation | Backpropagation learning rule with momentum. | Class | org.neuroph.nnet.learning | Neuroph |
| OjaLearning | Oja learning rule wich is a modification of unsupervised hebbian learning. | Class | org.neuroph.nnet.learning | Neuroph |
| OutstarLearning | Hebbian-like learning rule for Outstar network. | Class | org.neuroph.nnet.learning | Neuroph |
| PerceptronLearning | Perceptron learning rule for perceptron neural networks. | Class | org.neuroph.nnet.learning | Neuroph |
| RBFLearning | Learning rule for Radial Basis Function networks. | Class | org.neuroph.nnet.learning | Neuroph |
| ResilientPropagation | Resilient Propagation learning rule used for Multi Layer Perceptron neural networks. | Class | org.neuroph.nnet.learning | Neuroph |
| SigmoidDeltaRule | Delta rule learning algorithm for perceptrons with sigmoid (or any other diferentiable continuous) functions. | Class | org.neuroph.nnet.learning | Neuroph |
| SimulatedAnnealingLearning | This class implements a simulated annealing learning rule for supervised neural networks. | Class | org.neuroph.nnet.learning | Neuroph |
| SupervisedHebbianLearning | Supervised hebbian learning rule. | Class | org.neuroph.nnet.learning | Neuroph |
| UnsupervisedHebbianLearning | Unsupervised hebbian learning rule. | Class | org.neuroph.nnet.learning | Neuroph |