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 |