https://github.com/kosyoshida/TSKCCA

https://github.com/kosyoshida/TSKCCA

Last synced: 28 days ago
JSON representation

• Host: GitHub
• URL: https://github.com/kosyoshida/TSKCCA
• Owner: kosyoshida
• Created: 2016-12-04T08:33:11.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2018-06-16T00:15:54.000Z (about 6 years ago)
• Last Synced: 2023-10-19T23:23:04.037Z (9 months ago)
• Language: Matlab
• Size: 5.86 KB
• Stars: 6
• Watchers: 1
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Lists

• awesome-multi-omics - TSKCCA - Yoshida - Sparse kernel canonical correlation analysis - [paper](https://doi.org/10.1186/s12859-017-1543-x) (Software packages and methods / Multi-omics correlation or factor analysis)

README

        
# TSKCCA

Matlab code for two-stage kernel cca

Canonical correlation analysis (CCA) is a statistical tool for finding linear associations between different types of information. 

Previous extensions of CCA used to capture nonlinear associations, such as kernel CCA, did not allow feature selection or capturing of multiple canonical components. 

Here we propose a novel method, two-stage kernel CCA (TSKCCA) to select appropriate kernels in the framework of multiple kernel learning.

reference