Classes |
class | Node |
| A node in a self-organizing map. More...
|
class | NodeAndDistance |
| Used for creating an array of nodes sorted by nearness to a source node. More...
|
class | NodeLocationInitialization |
| Way of initializing the node positions according to a given topology - for example: points on a grid, on a triangular lattice, or random points in space. More...
|
class | GridTopology |
| Set the nodes to lie on an integer grid within the given maxima. A grid with 10,10 maximum is assumed to go from 0..9. NOTE: if the difference between a dimensional maximum and the nearest integer is less than 1e-6 then the maximum is taken to be that integer. Otherwise it is taken to be the maximum rounded down. More...
|
class | NodeWeightInitialization |
| Algorithm to initialize the weights of the nodes in the network before training. More...
|
class | NodeWeightInitializationTrainingSetSample |
| Initializes the weights to a random sample of rows from the training set. More...
|
class | Reporter |
| Reports periodically on the training of a self-organizing map - writing status to a stream every so many seconds or iterations, writing visualizations of the network or the network itself to sequentially named files. More...
|
class | IterationIntervalReporter |
| Calls its sub-reporter on start, the first iteration of a block of "interval" iterations, and finally on stop. More...
|
class | ReporterChain |
| A ReporterChain contains a list of Reporter objects. When a method is called on the ReporterChain, it calls the same method on each of its sub-objects in turn. More...
|
class | SVG2DWeightReporter |
| Writes out sequentially numbered svg files giving the weight locations in 2 dimensions of input space connected by a mesh that connects each weight with its nearest neighbors. Writes one file each time newStatus is called and once when stop is called. The output of stop may duplicate the last newStatus's output, but is not guaranteed to. More...
|
class | NoReporting |
| A reporter that does nothing. More...
|
class | NeighborhoodWindowFunction |
| Function that given a width, and a distance from the center of the neighborhood returns a weight to be used to calculate the influence of neighboring nodes at that distance. For each radius, can tell a distance d (possibly infinity) from the center for which all weights for distances greater than or equal to d will be 0. More...
|
class | GaussianWindowFunction |
| Uses a unit-height, zero-mean Gaussian weighting with the width as sigma truncated to 0 at 5 standard deviations. More...
|
class | UniformWindowFunction |
| Uses a unit-height, zero-mean Uniform weighting with the width being the radius of the circle anything beyond width is 0. More...
|
class | TrainingAlgorithm |
| An algorithm for training self-organizing maps. Before training is started, it is expected that the nodes are allocated and that the geometry of the map has been set by giving each node a position and a distance function. However, the weight vectors and the output dimensionality will be completely overwritten by training. More...
|
class | DummyTrainingAlgorithm |
| A training algorithm that throws an exception when train is called - stub for fully serializing training algorithms. More...
|
class | BatchTraining |
| Implements the batch training algorithm for self-organizing maps as described in T. Kohonen "Self Organizing Maps" Third Edition, 2001, published by Springer. More...
|
class | TraditionalTraining |
| Implments the traditional step-wise training of self-organized maps //TODO: finish this comment. More...
|