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Found 4 papers, 2 papers with code
Review of Clustering Methods for Functional Data
We propose a systematic taxonomy that explores the connections and differences among the existing functional data clustering methods and relates them to the conventional multivariate clustering methods.
Bayesian Optimisation for Sequential Experimental Design with Applications in Additive Manufacturing
This work aims to bring attention to the benefits of applying BO in designing experiments and to provide a BO manual, covering both methodology and software, for the convenience of anyone who wants to apply or learn BO.
Clustering of Big Data with Mixed Features
The improvements are threefold: (1) the new algorithm is applicable to mixed data; (2) the algorithm is capable of detecting outliers and clusters of relatively lower density values; (3) the algorithm is competent at deciding the correct number of clusters.
Weighted Clustering Ensemble: A Review
Clustering ensemble, or consensus clustering, has emerged as a powerful tool for improving both the robustness and the stability of results from individual clustering methods.
