class
This package provides functions for classification.
Functions
Function | Description |
---|---|
SOM, batchSOM | Kohonen’s self-organizing maps (SOMs) are a crude form of multidimensional scaling. |
condense | Condenses training set for k-nearest-neighbor (k-NN) classifier. |
knn | k-nearest-neighbor classification
for test set from training set. For each row of the test set,
the k -nearest (in Euclidean
distance) training set vectors are found, and the
classification is decided by majority vote, with ties broken
at random. If there are ties for the k th nearest vector, all
candidates are included in the vote. |
knn.cv | k-nearest-neighbor cross-validatory classification from training set. |
knn1 | Nearest-neighbor classification for test set from training set. For each row of the test set, the nearest neighbor (by Euclidean distance) training set vector is found, and its classification used. If there is more than one nearest neighbor, a majority vote is used, with ties broken at random. |
lvq1, lvq2, lvq3 | Moves examples in a codebook to better represent the training set. |
lvqinit | Constructs an initial codebook for learning vector quantization (LVQ) methods. |
lvqtest | Classifies a test set by 1-NN from a specified LVQ codebook. |
multiedit | Multiedit for k-NN classifier. |
olvq1 | Moves examples in a codebook to better represent the training set. |
reduce.nn | Reduces training set for a k-NN
classifier. Used after condense . |
somgrid | Plotting functions for SOM results. |
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