FLXMCLsvm: Mixtures of Support Vector Machines

In schiffner/locClass: Collection of Local Classification Methods

Description

This is a model driver for flexmix implementing mixtures of Support Vector Machines for classification.

Usage

FLXMCLsvm(formula = . ~ ., ...)

## S4 method for signature 'FLXMCLsvm'
FLXgetModelmatrix(model, data, formula, lhs = TRUE, ...)

Arguments

formula	A formula which is interpreted relative to the formula specified in the call to flexmix using update.formula. Only the left-hand side (response) of the formula is used. Default is to use the original flexmix model formula.
...	Further arguments to and from other methods, especially to wsvm.

Value

Returns an object of class FLXMCLsvm inheriting from FLXMCL.

See Also

Other mixtures svm: FLXMCL-class, FLXPwlda

Other mixtures svm: FLXMCL-class, FLXPwlda

Examples

library(benchData)
data <- flashData(1000)
data$x <- scale(data$x)
grid <- expand.grid(x.1 = seq(-6,6,0.2), x.2 = seq(-4,4,0.2))

cluster <- kmeans(data$x, center = 2)$cluster
model <- FLXMCLsvm(kernel = "linear", fitted = FALSE)
fit <- flexmix(y ~ ., data = as.data.frame(data), concomitant = FLXPmultinom(~ x.1 + x.2), model = model, cluster = cluster)

## prediction for single component models without aggregation
pred.grid <- predict(fit, newdata = grid)
image(seq(-6,6,0.2), seq(-4,4,0.2), matrix(pred.grid[[1]][,1], length(seq(-6,6,0.2))))
contour(seq(-6,6,0.2), seq(-4,4,0.2), matrix(pred.grid[[1]][,1], length(seq(-6,6,0.2))), add = TRUE)
points(data$x, pch = as.character(data$y))

image(seq(-6,6,0.2), seq(-4,4,0.2), matrix(pred.grid[[2]][,1], length(seq(-6,6,0.2))))
contour(seq(-6,6,0.2), seq(-4,4,0.2), matrix(pred.grid[[2]][,1], length(seq(-6,6,0.2))), add = TRUE)
points(data$x, pch = as.character(data$y))

## prediction with aggregation depending on membership in mixture components
pred.grid <- mypredict(fit, newdata = grid, aggregate = TRUE)
image(seq(-6,6,0.2), seq(-4,4,0.2), matrix(pred.grid[[1]][,1], length(seq(-6,6,0.2))))
contour(seq(-6,6,0.2), seq(-4,4,0.2), matrix(pred.grid[[1]][,1], length(seq(-6,6,0.2))), add  = TRUE)
points(data$x, pch = as.character(data$y))

## local membership
loc.grid <- prior(fit, newdata = grid)
contour(seq(-6,6,0.2), seq(-4,4,0.2), matrix(loc.grid[,1], length(seq(-6,6,0.2))), add  = TRUE)

schiffner/locClass documentation built on May 29, 2019, 3:39 p.m.