qtSNE-class {qkerntool} | R Documentation |
Class "qtSNE"
Description
An S4 Class for qtSNE.
Details
The qtSNE is a method that uses Qkernel t-Distributed Stochastic Neighborhood Embedding between the distance matrices in high and low-dimensional space to embed the data. The method is very well suited to visualize complex structures in low dimensions.
Objects from the Class
Objects can be created by calls of the form new("qtSNE", ...)
.
or by calling the function qtSNE
.
Slots
dimRed
Matrix containing the new representations for the objects after qtSNE
cndkernf
The kernel function used
Method
dimRed
signature(object="qtSNE")
: return a new representation matrixcndkernf
signature(object="qtSNE")
: return the kernel used
Author(s)
Yusen Zhang
yusenzhang@126.com
References
Maaten, L. van der, 2014. Accelerating t-SNE using Tree-Based Algorithms. Journal of Machine Learning Research 15, 3221-3245.
van der Maaten, L., Hinton, G., 2008. Visualizing Data using t-SNE. J. Mach. Learn. Res. 9, 2579-2605.
See Also
Examples
## Not run:
#use iris data set
data(iris)
testset <- sample(1:150,20)
train <- as.matrix(iris[,1:4])
colors = rainbow(length(unique(iris$Species)))
names(colors) = unique(iris$Species)
#for matrix
ecb = function(x,y){
plot(x,t='n');
text(x,labels=iris$Species, col=colors[iris$Species])
}
kpc2 <- qtSNE(train, kernel = "rbfbase", qpar = list(sigma=1,q=0.8),
epoch_callback = ecb, perplexity=10, max_iter = 500)
#cndernf
cndkernf(kpc2)
#dimRed
plot(dimRed(kpc2),col=train)
## End(Not run)