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Robust continuum regression

The development of new data analysis methods is also an important area of QSAR research. Several methods have been developed in recent years, and these include kernel partial least squares (K-PLS) [92], robust continuum regression [93], local lazy regression [94], fuzzy interval number -nearest neighbor (FINkNN) [95], and fast projection plane classifier (FPPC) [96], These methods have been shown to be useful for the prediction of a wide variety of target properties, which include moisture, oil, protein and starch... [Pg.232]

Semeels S, Filzmoser P, Croux C, Van Espen PJ. Robust continuum regression. Chemom Intell Lab Sys 2005 76 197-204. [Pg.238]


See other pages where Robust continuum regression is mentioned: [Pg.63]    [Pg.126]    [Pg.476]   
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