Ensemble method for cluster number determination and algorithm selection in unsupervised learning [version 1; peer review: 2 approved with reservations, 1 not approved]

• Published in: F1000 research Vol. 11; p. 573
• Main Author: Zambelli, Antoine
• Format: Journal Article
• Language: English
• Published: 2022
• Subjects: K-means; Gaussian Mixture; Number of Clusters; Ensemble; Consensus Clustering; Hierarchical Clustering; Spectral Clustering; Unsupervised Learning; Clustering

Unsupervised learning, and more specifically clustering, suffers from the need for expertise in the field to be of use. Researchers must make careful and informed decisions on which algorithm to use with which set of hyperparameters for a given dataset. Additionally, researchers may need to determin...