Learning Approximate Sequential Patterns for Classification

Learning Approximate Sequential Patterns for Classification

In this paper, we present an automated approach to discover patterns that can distinguish between sequences belonging to different labeled groups. Our method searches for approximately conserved motifs that occur with varying statistical properties in positive and negative training examples. We prop...

Full description

Bibliographic Details
Main Authors: Syed, Zeeshan (Author), Indyk, Piotr (Contributor), Guttag, John V. (Contributor)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
Format: Article
Language:English
Published: MIT Press, 2011-06-09T18:10:07Z.
Subjects:
Article
Online Access:Get fulltext

Internet

Get fulltext

Similar Items