Application of Bio-inspired Methods Within Cluster Forest Algorithm

被引:2
作者
Janousek, Jan [1 ]
Gajdos, Petr [1 ]
Radecky, Michal [1 ]
Snasel, Vaclav [1 ]
机构
[1] VSB Tech Univ Ostrava, FEECS, Dept Comp Sci, Ostrava, Czech Republic
来源
PROCEEDINGS OF THE SECOND INTERNATIONAL AFRO-EUROPEAN CONFERENCE FOR INDUSTRIAL ADVANCEMENT (AECIA 2015) | 2016年 / 427卷
关键词
Cluster Forest; Clustering; Ensemble clustering; Optimization; Soft computing; OPTIMIZATION;
D O I
10.1007/978-3-319-29504-6_24
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cluster Forest (CF) is relatively new ensemble clustering method inspired by Random Forest algorithm. The main idea behind of the existing algorithm consists in a construction of a larger number of partial clusterings for feature subsets using K-means algorithm. At the end, these clusterings are aggregated using a method of spectral clustering. This article describes a newapplication of bio-inspired methods that replaces the K-means algorithm in the computation pipeline. Several bio-inspired methods were tested on eight different datasets and compared with the original CF and others well known clustering methods.
引用
收藏
页码:237 / 247
页数:11
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