Natural neighborhood graph-based instance reduction algorithm without parameters

2018 ◽  
Vol 70 ◽  
pp. 279-287 ◽  
Author(s):  
Lijun Yang ◽  
Qingsheng Zhu ◽  
Jinlong Huang ◽  
Dongdong Cheng ◽  
Quanwang Wu ◽  
...  
Keyword(s):  
Reduction Algorithm ◽  
Neighborhood Graph ◽  
Instance Reduction

Natural Neighbor Reduction Algorithm for Instance-based Learning

2016 ◽  
Vol 10 (4) ◽  
pp. 59-73 ◽  
Author(s):  
Lijun Yang ◽  
Qingsheng Zhu ◽  
Jinlong Huang ◽  
Dongdong Cheng ◽  
Cheng Zhang
Keyword(s):  
Classification Accuracy ◽  
Hybrid Approach ◽  
Reduction Algorithm ◽  
Storage Space ◽  
Computational Costs ◽  
Condensation Method ◽  
Instance Reduction ◽  
Instance Based Learning ◽  
Natural Neighbor ◽  
Competitive Algorithms

Instance reduction is aimed at reducing prohibitive computational costs and the storage space for instance-based learning. The most frequently used methods include the condensation and edition approaches. Condensation method removes the patterns far from the decision boundary and do not contribute to better classification accuracy, while edition method removes noisy patterns to improve the classification accuracy. In this paper, a new hybrid algorithm called instance reduction algorithm based on natural neighbor and nearest enemy is presented. At first, an edition algorithm is proposed to filter noisy patterns and smooth the class boundaries by using natural neighbor. The main advantage of the algorithm is that it does not require any user-defined parameters. Then, using a new condensation method based on nearest enemy to reduce instances far from decision line. Through this algorithm, interior instances are discarded. Experiments show that the hybrid approach effectively reduces the number of instances while achieves higher classification accuracy along with competitive algorithms.

LMIRA: Large Margin Instance Reduction Algorithm

2014 ◽  
Vol 145 ◽  
pp. 477-487 ◽  
Author(s):  
Javad Hamidzadeh ◽  
Reza Monsefi ◽  
Hadi Sadoghi Yazdi
Keyword(s):  
Reduction Algorithm ◽  
Large Margin ◽  
Instance Reduction

IRAHC: Instance Reduction Algorithm using Hyperrectangle Clustering

2015 ◽  
Vol 48 (5) ◽  
pp. 1878-1889 ◽  
Author(s):  
Javad Hamidzadeh ◽  
Reza Monsefi ◽  
Hadi Sadoghi Yazdi
Keyword(s):  
Reduction Algorithm ◽  
Instance Reduction

Application of an attribute reduction algorithm based on discernibility matrix in PBNM

2014 ◽  
Author(s):  
Shuo Feng ◽  
Haiying Chu ◽  
Xuyang Wang ◽  
Yuanka Liang ◽  
Xianwei Shi ◽  
...  
Keyword(s):  
Attribute Reduction ◽  
Reduction Algorithm ◽  
Discernibility Matrix

A New Lattice Reduction Algorithm Based on Genetic Strategy

2014 ◽  
Vol 35 (8) ◽  
pp. 1940-1945 ◽  
Author(s):  
Xiang-hui Liu ◽  
Wen-bao Han ◽  
Jian-xiao Quan
Keyword(s):  
Lattice Reduction ◽  
Reduction Algorithm
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