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Construct an initial codebook for LVQ methods.
● Data Source:
CranContrib
● Keywords: classif
● Alias: lvqinit
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Multiedit for k-NN classifier
● Data Source:
CranContrib
● Keywords: classif
● Alias: multiedit
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Reduce training set for a k-NN classifier. Used after condense.
● Data Source:
CranContrib
● Keywords: classif
● Alias: reduce.nn
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Kohonen's Self-Organizing Maps are a crude form of multidimensional scaling.
● Data Source:
CranContrib
● Keywords: classif
● Alias: SOM
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k-nearest neighbour 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, all candidates are included in the vote.
● Data Source:
CranContrib
● Keywords: classif
● Alias: knn
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Condense training set for k-NN classifier
● Data Source:
CranContrib
● Keywords: classif
● Alias: condense
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Moves examples in a codebook to better represent the training set.
● Data Source:
CranContrib
● Keywords: classif
● Alias: lvq2
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k-nearest neighbour cross-validatory classification from training set.
● Data Source:
CranContrib
● Keywords: classif
● Alias: knn.cv
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Nearest neighbour classification for test set from training set. For each row of the test set, the nearest (by Euclidean distance) training set vector is found, and its classification used. If there is more than one nearest, a majority vote is used with ties broken at random.
● Data Source:
CranContrib
● Keywords: classif
● Alias: knn1
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Classify a test set by 1-NN from a specified LVQ codebook.
● Data Source:
CranContrib
● Keywords: classif
● Alias: lvqtest
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providing 
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