k nearest neighbor algorithm for multi-variate data
k nearest neighbor algorithm for multi-variate data
knn(X, K = 2, init, Ninit = 50, verbose = FALSE, tol, Niter.max = 500)
X |
data matrix, i.e. observations X dimensions |
K |
number of clusters to use |
init |
list of p and mu used for initialization |
Ninit |
number of samples used per cluster if no init argument is given |
verbose |
allows print out of progress information; in verbose mode the cluster memberships are added to the output |
tol |
smaller changes than tol in the objective function indicate convergence, if missing chosen automatically to be 1/5 of the smallest sample variance per dimension |
maxIter |
maximum number of admissible iterations |
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.