Hydrological classification by clustering approach of time-integrated samples at the outlet of the Rhône River: Application to Δ14C-POC

Multivariate analysis for data mining to characterize poultry house environment in winter

“…A useful approach to k-means clustering for determining the optimal number of clusters in data without prior knowledge is to run different simulations with different k values and then use the silhouette method to assess clustering efficiency. Based on previous studies ( Javed et al, 2021 ; Bodereau et al, 2022 ) and our preliminary observations, we set the test interval for the k values as [2, 8]. This test interval was also used for k-medoids and the fuzzy c-means clustering, as discussed in the following sections.…”