Rdimtools (version 0.3.2)

do.klsda: Kernel Locality Sensitive Discriminant Analysis

Description

Kernel LSDA (KLSDA) is a nonlinear extension of LFDA method using kernel trick. It applies conventional kernel method to extend excavation of hidden patterns in a more flexible manner in tradeoff of computational load. For simplicity, only the gaussian kernel parametrized by its bandwidth t is supported.

Usage

do.klsda(X, label, ndim = 2, preprocess = c("center", "scale", "cscale",
  "whiten", "decorrelate"), alpha = 0.5, k1 = max(ceiling(nrow(X)/10), 2),
  k2 = max(ceiling(nrow(X)/10), 2), t = 1)

Arguments

X

an \((n\times p)\) matrix or data frame whose rows are observations and columns represent independent variables.

label

a length-\(n\) vector of data class labels.

ndim

an integer-valued target dimension.

preprocess

an additional option for preprocessing the data. Default is "center". See also aux.preprocess for more details.

alpha

balancing parameter for between- and within-class scatter in \([0,1]\).

k1

the number of same-class neighboring points (homogeneous neighbors).

k2

the number of different-class neighboring points (heterogeneous neighbors).

t

bandwidth parameter for heat kernel in \((0,\infty)\).

Value

a named list containing

Y

an \((n\times ndim)\) matrix whose rows are embedded observations.

trfinfo

a list containing information for out-of-sample prediction.

References

cai_locality_2007Rdimtools

Examples

# NOT RUN {
## generate 3 different groups of data X and label vector
x1 = matrix(rnorm(4*10), nrow=10)-50
x2 = matrix(rnorm(4*10), nrow=10)
x3 = matrix(rnorm(4*10), nrow=10)+50
X  = rbind(x1, x2, x3)
label = c(rep(1,10), rep(2,10), rep(3,10))

## try different kernel bandwidths
out1 = do.klsda(X, label, k1=10, k2=10, t=1)
out2 = do.klsda(X, label, k1=10, k2=10, t=5)
out3 = do.klsda(X, label, k1=10, k2=10, t=10)

## visualize
par(mfrow=c(1,3))
plot(out1$Y[,1], out1$Y[,2], main="bandwidth=1")
plot(out2$Y[,1], out2$Y[,2], main="bandwidth=15")
plot(out3$Y[,1], out3$Y[,2], main="bandwidth=10")

# }