Preprocessing for classification of thermograms in breast cancer detection
Łukasz Neumann , Robert Marek Nowak , Rafał Okuniewski , Witold Oleszkiewicz , Paweł Cichosz , Dariusz Jagodziński , Mateusz Matysiewicz
AbstractPerformance of binary classification of breast cancer suffers from high imbalance between classes. In this article we present the preprocessing module designed to negate the discrepancy in training examples. Preprocessing module is based on standardization, Synthetic Minority Oversampling Technique and undersampling. We show how each algorithm influences classification accuracy. Results indicate that described module improves overall Area Under Curve up to 10% on the tested dataset. Furthermore we propose other methods of dealing with imbalanced datasets in breast cancer classification.
|Publication size in sheets||0.5|
|Book||Romaniuk Ryszard (eds.): Proc. SPIE. 10031, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2016, vol. 10031, 2016, SPIE , ISBN 9781510604858, [781510604865 (electronic) ], 1170 p., DOI:10.1117/12.2257157|
|Score|| = 15.0, 27-03-2017, BookChapterMatConf|
= 15.0, 27-03-2017, BookChapterMatConf
|Citation count*||7 (2018-02-21)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.