Evaluation of Stability of k-Means Cluster Ensembles with Respect to Random Initialization

By Ludmila I. Kuncheva, Dmitry P. Vetrov. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006

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A survey on ensemble learning (2019, background): “Kuncheva and Whitaker [127] explored the relationship between diversity and accuracy of ensemble model, followed by investigating the stability of clustering ensemble algorithms with respect to various initialization parameters and conditions [128].”
A Kernel-Based Feature Selection Method for SVM With RBF Kernel for Hyperspectral Image Classification (2014, methodology): “To explore the robustness of the nonlinear problem, simple doughnut data [34], [35], a simulated two-class dataset containing two true features and ten uniformly random noise features was generated, as shown in Fig.”