A Simple Classification Method for Class Imbalanced Data using the Kernel Mean

2014 ◽  
Author(s):  
Yusuke Sato ◽  
Kazuyuki Narisawa ◽  
Ayumi Shinohara
Keyword(s):  
Imbalanced Data ◽  
Classification Method ◽  
Simple Classification

Imbalanced Data Classification Based on Clustering

2013 ◽  
Vol 443 ◽  
pp. 741-745
Author(s):  
Hu Li ◽  
Peng Zou ◽  
Wei Hong Han ◽  
Rong Ze Xia
Keyword(s):  
Real World ◽  
Imbalanced Data ◽  
Data Classification ◽  
Comprehensive Analysis ◽  
Classification Method ◽  
Classification Methods ◽  
Real World Data ◽  
Minority Class ◽  
Imbalanced Data Classification ◽  
Traditional Classification

Many real world data is imbalanced, i.e. one category contains significantly more samples than other categories. Traditional classification methods take different categories equally and are often ineffective. Based on the comprehensive analysis of existing researches, we propose a new imbalanced data classification method based on clustering. The method clusters both majority class and minority class at first. Then, clustered minority class will be over-sampled by SMOTE while clustered majority class be under-sampled randomly. Through clustering, the proposed method can avoid the loss of useful information while resampling. Experiments on several UCI datasets show that the proposed method can effectively improve the classification results on imbalanced data.

scholarly journals A Novel Classification Method for Class-imbalanced Data and Its Application in microRNA Recognition

2018 ◽  
Vol 22 (2) ◽  
pp. 133-146
Author(s):  
Xia Geng ◽  
◽  
Yu-Quan Zhu ◽  
Zhi Yang ◽  
◽  
...  
Keyword(s):  
Imbalanced Data ◽  
Classification Method
Sign in / Sign up

Export Citation Format

Share Document