@Article{jnm.2021.018267,
AUTHOR = {Mingming Yang, Junchuan Yang},
TITLE = {Feature Selection Based on Distance Measurement},
JOURNAL = {Journal of New Media},
VOLUME = {3},
YEAR = {2021},
NUMBER = {1},
PAGES = {19--27},
URL = {http://www.techscience.com/JNM/v3n1/41731},
ISSN = {2579-0129},
ABSTRACT = {Every day we receive a large amount of information through different 
social media and software, and this data and information can be realized with the 
advent of data mining methods. In the process of data mining, to solve some 
high-dimensional problems, feature selection is carried out in limited training 
samples, and effective features are selected. This paper focuses on two Relief 
feature selection algorithms: Relief and ReliefF algorithm. The differences 
between them and their respective applicable scopes are analyzed. Based on 
Relief algorithm, the high weight feature subset is obtained, and the correlation 
between features is calculated according to the mutual information distance 
measure, and the high redundant features are removed to obtain the feature 
subset with higher quality. Experimental results on six datasets show the 
effectiveness of our method.},
DOI = {10.32604/jnm.2021.018267}
}