"A divisive hierarchical clustering methodology for enhancing the ensemble ..."

Petros Barmpas et al. (2022)

> Home

Details and statistics

DOI: 10.1007/S13755-022-00171-1

access: closed

type: Journal Article

metadata version: 2024-08-04

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - journals/hisas/BarmpasTVGAPABB22
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/hisas/BarmpasTVGAPABB22
Petros Barmpas, Sotiris K. Tasoulis, Aristidis G. Vrahatis, Spiros V. Georgakopoulos, Panagiotis Anagnostou, Matthew Prina, José Luis Ayuso-Mateos, Jerome Bickenbach, Ivet Bayes, Martin Bobak, Francisco Félix Caballero, Somnath Chatterji, Laia Egea-Cortés, Esther García-Esquinas, Matilde Leonardi, Seppo Koskinen, Ilona Koupil, Andrzej Pajak, Martin Prince, Warren Sanderson, Sergei Scherbov, Abdonas Tamosiunas, Aleksander Galas, Josep Maria Haro, Albert Sanchez-Niubo, Vassilis P. Plagianakos, Demosthenes Panagiotakos:
A divisive hierarchical clustering methodology for enhancing the ensemble prediction power in large scale population studies: the ATHLOS project. Health Inf. Sci. Syst. 10(1): 6 (2022)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.