Apr 20, 2016 · Abstract. We study the cluster ensemble problem and propose a cluster ensemble approach based on subspace similarity (CEASS).
We study the cluster ensemble problem and propose a cluster ensemble approach based on subspace similarity (CEASS). From a subspace similarity perspective, ...
A novel cluster ensemble approach effected by subspace similarity. S. Xu, K. Chan, T. Zhou, J. Gao, X. Li, and X. Hua. Intell. Data Anal., 20 (3): 561-574 ...
Jun 5, 2024 · The paper proposes a novel subspace-based GMM clustering ensemble (SubGMM-CE) algorithm tailored for HDD.
Missing: effected | Show results with:effected
Nov 19, 2016 · The main goal of clustering is to partition the dataset (also called pattern set, point set or object set) into natural groups or clusters such ...
Missing: effected | Show results with:effected
all rough subspaces of categorical data. Subsequently, a novel clustering ensemble method based on selected rough subspaces is introduced to deal with ...
We present a novel geometric approach to the subspace clustering problem that leverages ensembles of the K-subspace (KSS) algorithm via the evidence ...
Missing: effected | Show results with:effected
This paper presents a novel, highly effective link-based cluster ensemble approach(WTQ) to categorical data clustering. It transforms the original ...
Missing: effected | Show results with:effected
May 24, 2022 · We combine subspace clustering and ensemble learning to propose a novel subspace weighted clustering ensemble framework for high-dimensional data.
Missing: effected | Show results with:effected
Jan 16, 2018 · A clustering ensemble aims to combine multiple clustering models to produce a better result than that of the individual clustering algorithms in terms of ...
Missing: effected | Show results with:effected