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Abstract Details

Activity Number: 33
Type: Contributed
Date/Time: Sunday, July 29, 2012 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Learning and Data Mining
Abstract - #306007
Title: Multi-Scale Geometry and Motif Matching in Relational Data Learning
Author(s): Hui Wang*+
Companies: University of California at Davis
Address: 5000 Orchard Park Circle, Davis, CA, 95616, United States
Keywords: Data Cloud Geometry ; functional MRI data ; Motif Matching ; Classification ; Clustering ; Learning
Abstract:

We propose multi-scale geometry and motif matching, a method to implement classification for relational data. By utilizing data cloud geometry, we obtain a scale-sensitive hierarchical geometry, then by matching the geometry, we calculate the distance between subjects, and use it as a metric for classification. Multi-scale geometry and motif matching is illustrated for the analysis of functional MRI correlation data in diagnosis for autism spectrum disorder (ASD).


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