Discriminant Adaptive Nearest Neighbor With Subspace Reduction
sub_dann(
x,
...,
k = 5,
neighborhood_size = max(floor(nrow(x)/5), 50),
epsilon = 1,
weighted = FALSE,
sphere = "mcd",
numDim = ceiling(ncol(x)/2)
)An S3 class of type sub_dann
A matrix or a dataframe.
Additional parameters passed to methods.
The number of data points used for final classification.
The number of data points used to calculate between and within class covariance.
Diagonal elements of a diagonal matrix. 1 is the identity matrix.
weighted argument to ncoord. See fpc::ncoord() for details.
One of "mcd", "mve", "classical", or "none" See fpc::ncoord() for details.
Dimension of subspace used by dann. See fpc::ncoord() for details.
An implementation of Hastie and Tibshirani's sub-dann in section 4.1 of Discriminant Adaptive Nearest Neighbor Classification publication..
dann's performance suffers when noise variables are included in the model. Simulations show sub_dann will generally be more performant in this scenario.