A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Multi-objective clustering ensemble for high-dimensional data based on Strength Pareto Evolutionary Algorithm (SPEA-II)
2015
2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA)
Clustering is one of the fundamental data analysis techniques, which aims to find distinct groups of similar objects and discovers hidden structures in data. A recent clustering approach, clustering ensembles tries to derive an improved clustering solution based on previously generated different candidate clustering solutions. Clustering ensembles have two steps: generating multiple candidate clustering solutions from the data and forming a final clustering solution from previously generated
doi:10.1109/dsaa.2015.7344795
dblp:conf/dsaa/WahidGA15
fatcat:gmyjaw2ltre3vdsel5ejy3l3dq