R in a Nutshell, 2nd Edition

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 kth nearest vector, then 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.