Skip to content

aicip/GDT

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 
 
 

Repository files navigation

GDT

A demo of Gaussian-based Decision Tree, which is designed for classification on small dataset, e.g., there are only two sample for training in each category.

Pre-requisite

  • Matlab

Run the demo

>> demo

The result will be printed like

Accuracy (std) of GDT vs. DT:
	GDT	0.75 (0.10)
	DT	0.50 (0.11)

It may vary for each run because the random selection of training samples.

Citation

Z. Zhang, Y. Song, H. Cui, J. Wu, F. Schwartz, and H. Qi. "Topological Analysis and Gaussian Decision Tree: Effective Representation and Classification of Biosignals of Small Sample Size". IEEE Transactions on Biomedical Engineering (TBME), 2016. [PDF]

Z. Zhang, Y. Song, H. Cui, J. Wu, F. Schwartz, and H. Qi. "Early Mastitis Diagnosis through Topological Analysis of Biosignalsfrom Low-Voltage Alternate Current Electrokinetics". International Conference on the IEEE Engineering in Medicine and Biology Society (EMBC), 2015. [PDF]

@inproceedings{zhang2015early,
  title={Early mastitis diagnosis through topological analysis of biosignals from low-voltage alternate current electrokinetics},
  author={Zhang, Zhifei and Song, Yang and Cui, Haochen and Wu, Jayne and Schwartz, Fernando and Qi, Hairong},
  booktitle={2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},
  pages={542--545},
  year={2015},
  organization={IEEE}
}

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages