@article{M03818A6D,
title = "Creating Level Set Trees Using One-Class Support Vector Machines",
journal = "Journal of KIISE, JOK",
year = "2015",
issn = "2383-630X",
doi = "",
author = "Gyemin Lee",
keywords = "one-class support vector machines,level set tree,solution path algorithm,clustering,visualization",
abstract = "A level set tree provides a useful representation of a multidimensional density function. Visualizing the data structure as a tree offers many advantages for data analysis and clustering. In this paper, we present a level set tree estimation algorithm for use with a set of data points. The proposed algorithm creates a level set tree from a family of level sets estimated over a whole range of levels from zero to infinity. Instead of estimating density function then thresholding, we directly estimate the density level sets using one-class support vector machines (OC-SVMs). The level set estimation is facilitated by the OC-SVM solution path algorithm. We demonstrate the proposed level set tree algorithm on benchmark data sets."
}