References in zbMATH (referenced in 25 articles , 1 standard article )

Showing results 1 to 20 of 25.
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  1. Deswal, Sumit; Bulusu, Krishna C.; Agapow, Paul-Michael; Khan, Faisal M.: Precision medicine (2021)
  2. Freitas, Adelaide; Macedo, Eloísa; Vichi, Maurizio: An empirical comparison of two approaches for CDPCA in high-dimensional data (2021)
  3. Gündüz, Necla; Fokoué, Ernest: Understanding students’ evaluations of professors using non-negative matrix factorization (2021)
  4. Lim, David K.; Rashid, Naim U.; Ibrahim, Joseph G.: Model-based feature selection and clustering of RNA-seq data for unsupervised subtype discovery (2021)
  5. Michael C. Thrun, Quirin Stier: Fundamental clustering algorithms suite (2021) not zbMATH
  6. Saunders, K. R.; Stephenson, A. G.; Karoly, D. J.: A regionalisation approach for rainfall based on extremal dependence (2021)
  7. Thrun, Michael C.; Ultsch, Alfred: Using projection-based clustering to find distance- and density-based clusters in high-dimensional data (2021)
  8. Tsai, Cary Chi-Liang; Cheng, Echo Sihan: Incorporating statistical clustering methods into mortality models to improve forecasting performances (2021)
  9. van Delft, Anne; Dette, Holger: A similarity measure for second order properties of non-stationary functional time series with applications to clustering and testing (2021)
  10. Boehmke, Brad; Greenwell, Brandon M.: Hands-on machine learning with R (2020)
  11. Fu, Wei; Perry, Patrick O.: Estimating the number of clusters using cross-validation (2020)
  12. Giordani, Paolo; Ferraro, Maria Brigida; Martella, Francesca: An introduction to clustering with R (2020)
  13. Isotta Landi, Veronica Mandelli, Michael V. Lombardo: reval: a Python package to determine the best number of clusters with stability-based relative clustering validation (2020) arXiv
  14. Rivas-Tabares, David; de Miguel, Ángel; Willaarts, Bárbara; Tarquis, Ana M.: Self-organizing map of soil properties in the context of hydrological modeling (2020)
  15. Talebi, H.; Peeters, L. J. M.; Mueller, U.; Tolosana-Delgado, R.; van den Boogaart, K. G.: Towards geostatistical learning for the geosciences: a case study in improving the spatial awareness of spectral clustering (2020)
  16. François Role, Stanislas Morbieu, Mohamed Nadif: CoClust: A Python Package for Co-Clustering (2019) not zbMATH
  17. He, Zhenfeng; Yu, Chunyan: Clustering stability-based evolutionary K-means (2019)
  18. Kharoubi, Rachid; Oualkacha, Karim; Mkhadri, Abdallah: The cluster correlation-network support vector machine for high-dimensional binary classification (2019)
  19. Mair, Patrick: Modern psychometrics with R (2018)
  20. Plaza, Francisco; Salas, Rodrigo; Yáñez, Eleuterio: Identifying ecosystem patterns from time series of anchovy (\textitEngraulisringens) and sardine (\textitSardinopssagax) landings in northern Chile (2018)

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