Kernel classification of connectomes based on earth mover's distance between graph spectra

11/27/2016
by   Yulia Dodonova, et al.
0

In this paper, we tackle a problem of predicting phenotypes from structural connectomes. We propose that normalized Laplacian spectra can capture structural properties of brain networks, and hence graph spectral distributions are useful for a task of connectome-based classification. We introduce a kernel that is based on earth mover's distance (EMD) between spectral distributions of brain networks. We access performance of an SVM classifier with the proposed kernel for a task of classification of autism spectrum disorder versus typical development based on a publicly available dataset. Classification quality (area under the ROC-curve) obtained with the EMD-based kernel on spectral distributions is 0.71, which is higher than that based on simpler graph embedding methods.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/12/2020

Gaussian Processes on Graphs via Spectral Kernel Learning

We propose a graph spectrum-based Gaussian process for prediction of sig...
research
12/07/2020

The Spectral-Domain 𝒲_2 Wasserstein Distance for Elliptical Processes and the Spectral-Domain Gelbrich Bound

In this short note, we introduce the spectral-domain 𝒲_2 Wasserstein dis...
research
08/18/2020

Ordinal Pattern Kernel for Brain Connectivity Network Classification

Brain connectivity networks, which characterize the functional or struct...
research
11/01/2021

Graph Structural Attack by Spectral Distance

Graph Convolutional Networks (GCNs) have fueled a surge of interest due ...
research
12/19/2019

A Maximum Entropy approach to Massive Graph Spectra

Graph spectral techniques for measuring graph similarity, or for learnin...
research
06/06/2023

Graph Classification Gaussian Processes via Spectral Features

Graph classification aims to categorise graphs based on their structure ...
research
10/22/2018

A Simple Baseline Algorithm for Graph Classification

Graph classification has recently received a lot of attention from vario...

Please sign up or login with your details

Forgot password? Click here to reset