Ensemble Clustering based on Heterogeneous Dimensionality Reduction Methods and Context-dependent Similarity Measures
Augustine Shey Nsang, Irene Dı́az, Anca Ralescu · International Journal of Advanced Science and Technology · 2014
This paper discusses one method of clustering a high dimensional dataset using dimensionality reduction and context dependency measures (CDM).First, the dataset is partitioned into a predefined number of clusters using CDM.Then, context dependency measures are combined with several dimensionality reduction techniques and for each choice the data set is clustered again.The results are combined by the cluster ensemble approach.Finally, the Rand index is used to compute the extent to which the clustering of the original dataset (by CDM alone) is preserved by the cluster ensemble approach.