deletions | additions       diff --git a/Related_workTraditional_Clustering_algorithms_can__.html b/Related_workTraditional_Clustering_algorithms_can__.html  index 982b45b..b671278 100644  --- a/Related_workTraditional_Clustering_algorithms_can__.html  +++ b/Related_workTraditional_Clustering_algorithms_can__.html 
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author = {Tamer F. Ghanem and Wail S. Elkilani and Hatem M. Abdul-kader},  title = {A hybrid approach for efficient anomaly detection using metaheuristic methods},  journal = {Journal of Advanced Research}  }" data-bib-key="Ghanem_2015" style="cursor: pointer" contenteditable="false">(Ghanem 2015) noise can be detected using these clustering methods, they are not scale well with the size of dataset. Finally, Grid-based clustering algorithms partition data space into grid of cells cells (Ghanem 2015)  which are combined to form clusters based on neighborhood relations. It is distinguished by fastness but it does not work efficiently in high dimensional space.

 

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Unlike Traditional clustering algorithms, subspace clustering has been proposed to overcome problems arisen from curse of dimensionality phenomena by constructing clusters based on similarities on a subset of attributes (subspace). As a result, some samples may be assigned to multiple clusters. If each sample is assigned to only one cluster based on some subset of attributes, subspace clustering will be called projected clustering.