som.nn-package |
Topological k-NN Classifier Based on Self-Organising Maps |
dist.fun.bubble |
Bubble distance functions for topological k-NN classifier |
dist.fun.inverse |
Inverse exponential distance functions for topological k-NN classifier |
dist.fun.linear |
Linear distance functions for topological k-NN classifier |
dist.fun.tricubic |
Tricubic distance functions for topological k-NN classifier |
dist.torus |
Torus distance matrix |
initialize-method |
Constructor of SOMnn Class |
norm.linear |
Linear normalisation |
norm.softmax |
Softmax normalisation |
plot-method |
Plot method for S4 class 'SOMnn' |
predict-method |
predict method for S4 class 'SOMnn' |
round.probabilities |
Advanced rounding of vectors |
som.nn |
Topological k-NN Classifier Based on Self-Organising Maps |
som.nn.accuracy |
Calculate accuracy measures |
som.nn.all.accuracy |
Calculate overall accuracy |
som.nn.confusion |
Calculate confusion matrix |
som.nn.continue |
Continue hexagonal som training |
som.nn.export.kohonen |
Export a som.nn model as object of type 'kohonen' |
som.nn.export.som |
Export a som.nn model as object of type 'SOM' |
som.nn.multitrain |
Multi-step hexagonal som training |
som.nn.set |
Set parameters for k-NN-like classifier in som.nn model |
som.nn.train |
Hexagonal som training |
som.nn.validate |
Predict class labels for a validation dataset |
som.nn.visual |
Mapping function for SOMnn |
SOMnn |
An S4 class to hold a model for the topological classifier som.nn |
SOMnn-class |
An S4 class to hold a model for the topological classifier som.nn |