UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

High-dimensional cluster analysis with the masked EM algorithm.

Kadir, SN; Goodman, DF; Harris, KD; (2014) High-dimensional cluster analysis with the masked EM algorithm. Neural Comput , 26 (11) 2379 - 2394. 10.1162/NECO_a_00661. Green open access

[thumbnail of NECO_a_00661-Kadir.pdf]
Preview
PDF
NECO_a_00661-Kadir.pdf

Download (568kB)

Abstract

Cluster analysis faces two problems in high dimensions: the "curse of dimensionality" that can lead to overfitting and poor generalization performance and the sheer time taken for conventional algorithms to process large amounts of high-dimensional data. We describe a solution to these problems, designed for the application of spike sorting for next-generation, high-channel-count neural probes. In this problem, only a small subset of features provides information about the cluster membership of any one data vector, but this informative feature subset is not the same for all data points, rendering classical feature selection ineffective. We introduce a "masked EM" algorithm that allows accurate and time-efficient clustering of up to millions of points in thousands of dimensions. We demonstrate its applicability to synthetic data and to real-world high-channel-count spike sorting data.

Type: Article
Title: High-dimensional cluster analysis with the masked EM algorithm.
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1162/NECO_a_00661
Publisher version: http://dx.doi.org/10.1162/NECO_a_00661
Language: English
Additional information: © 2014 Massachusetts Institute of Technology. Published under a Creative Commons Attribution 3.0 Unported (CC BY 3.0) license.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Department of Neuromuscular Diseases
URI: https://discovery.ucl.ac.uk/id/eprint/1447169
Downloads since deposit
113Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item