The Trace Criterion for Kernel Bandwidth Selection for Support Vector Data Description

no code implementations • 15 Nov 2018 • Arin Chaudhuri, Carol Sadek, Deovrat Kakde, Wenhao Hu, Hansi Jiang, Seunghyun Kong, Yuewei Liao, Sergiy Peredriy, Haoyu Wang

Support vector data description (SVDD) is a popular anomaly detection technique.

Anomaly Detection

The Mean and Median Criterion for Automatic Kernel Bandwidth Selection for Support Vector Data Description

no code implementations • 16 Aug 2017 • Arin Chaudhuri, Deovrat Kakde, Carol Sadek, Laura Gonzalez, Seunghyun Kong

The computation of the SVDD classifier requires a kernel function, and the Gaussian kernel is a common choice for the kernel function.

Sampling Method for Fast Training of Support Vector Data Description

no code implementations • 16 Jun 2016 • Arin Chaudhuri, Deovrat Kakde, Maria Jahja, Wei Xiao, Hansi Jiang, Seunghyun Kong, Sergiy Peredriy

Support Vector Data Description (SVDD) is a popular outlier detection technique which constructs a flexible description of the input data.

Outlier Detection

Peak Criterion for Choosing Gaussian Kernel Bandwidth in Support Vector Data Description

no code implementations • 17 Feb 2016 • Deovrat Kakde, Arin Chaudhuri, Seunghyun Kong, Maria Jahja, Hansi Jiang, Jorge Silva

For example, it is observed that with a Gaussian kernel, as the value of kernel bandwidth is lowered, the data boundary changes from spherical to wiggly.

General Classification Outlier Detection