𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Partial least-squares regression and fuzzy clustering ? A joint approach

✍ Scribed by Jacobsen, Tove ;Kolset, Knut ;Vogt, Nils B.


Book ID
105118064
Publisher
Springer-Verlag
Year
1986
Weight
524 KB
Volume
89
Category
Article
ISSN
0344-838X

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


A least-squares approach to fuzzy linear
✍ Pierpaolo D'Urso; Tommaso Gastaldi πŸ“‚ Article πŸ“… 2000 πŸ› Elsevier Science 🌐 English βš– 124 KB

This paper deals with a new approach to fuzzy linear regression analysis. A doubly linear adaptive fuzzy regression model is proposed, based on two linear models: a core regression model and a spread regression model. The ΓΏrst one "explains" the centers of the fuzzy observations, while the second on

Significance regression: a statistical a
✍ Tyler R. Holcomb; HΓ₯kan Hjalmarsson; Manfred Morari; Matthew L. Tyler πŸ“‚ Article πŸ“… 1997 πŸ› John Wiley and Sons 🌐 English βš– 409 KB πŸ‘ 2 views

This paper presents a formal framework for deriving partial least squares algorithms from statistical hypothesis testing. This new formulation, significance regression (SR), leads to partial least squares for scalar output problems (PLS1), to a close approximation of a common multivariable partial l

Canonical partial least squaresβ€”a unifie
✍ Ulf G. Indahl; Kristian Hovde Liland; Tormod NΓ¦s πŸ“‚ Article πŸ“… 2009 πŸ› John Wiley and Sons 🌐 English βš– 303 KB πŸ‘ 1 views

## Abstract We propose a new data compression method for estimating optimal latent variables in multi‐variate classification and regression problems where more than one response variable is available. The latent variables are found according to a common innovative principle combining PLS methodolog