dann — dann • dann

Run Discriminant Adaptive Nearest Neighbors

Usage

dann(
  x,
  testx = NULL,
  y,
  k = 5,
  kmetric = NULL,
  epsilon = 1,
  fullw = FALSE,
  scalar = FALSE,
  iter = 1,
  covmin = 1e-04,
  cv = FALSE
)

Arguments

x: covariates matrix
testx: test covariate matrix
y: labels
k: number of clusters
kmetric: metric
epsilon: epsilon
fullw: Boolean
scalar: Boolean
iter: maximum number of iterations
covmin: cov
cv: boolean reflecting whether to cross-validate or not

Value

Predicted class labels

Examples

if (FALSE) { # \dontrun{
dann(x <- matrix(rnorm(120,1,.2)), testx <- glass.test$x, y <- matrix(rnorm(120,1,.5)),
epsilon = 1, fullw = FALSE, iter = 100,  covmin = 1e-04, cv = FALSE)
} # }