Title
Entropy and gravitation based dynamic radius nearest neighbor classification for imbalanced problem
Abstract
In imbalanced problems, the asymmetric number of samples in different classes brings great challenges to traditional classifiers, especially to the Nearest Neighbors (NN) classifiers. When NN-based classifier deals with imbalanced problems, the criterion of itself makes the classification result data-dependent, thus biasing towards the majority class. To overcome the drawback in NN-based classifiers, a meta heuristic NN-based algorithm named Gravitational Fixed Radius Nearest Neighbor classifier (GFRNN) is proposed to solve imbalanced problems by drawing on Newton’s law of universal gravitation. However, GFRNN still has three major problems including negligence of the distribution of samples, unreasonable calculation of data mass and improper distance metric. To this end, this paper proposes an Entropy and Gravitation based Dynamic Radius Nearest Neighbor algorithm (EGDRNN). Different from GFRNN, EGDRNN determines the radius in a dynamic and rapid way. EGDRNN uses entropy information to make samples at different locations have different importance. Finally, by utilizing a general Lp-norm to calculate the distance between two samples, the classification performance is greatly improved. The experimental result validates that the proposed EGDRNN not only achieves the highest classification accuracy but also takes the lowest time consuming among all comparison algorithms.
Year
DOI
Venue
2020
10.1016/j.knosys.2020.105474
Knowledge-Based Systems
Keywords
Field
DocType
Information entropy,Gravitational force,Nearest neighbor rules,Imbalanced problem,Lp-norm
k-nearest neighbors algorithm,Newton's law of universal gravitation,Data mining,Computer science,Meta heuristic,Algorithm,Metric (mathematics),Majority class,Classifier (linguistics),Entropy (information theory),Gravitation
Journal
Volume
ISSN
Citations 
193
0950-7051
1
PageRank 
References 
Authors
0.35
0
5
Name
Order
Citations
PageRank
Zhe Wang15020.04
Yanqiong Li210.35
Dongdong Li3158.34
Zonghai Zhu4113.54
Wenli Du517930.50