Extended Partial Least Squares

Versione 1.1.0.0 (49,9 KB) da David Laurí
Identification algorithm
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Aggiornato 13 mar 2014

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Over-fitting is caused when the variance of the error term dominates the prediction error of the model. The variance error term dominates when dealing with short and fat data sets, which is typical in batch processes.
E-PLS tackles over-fitting by minimizing a prediction error cost function with an expanded number of error terms.

Reference:
-Title: Expanded PLS algorithm: Modeling of Batch Processes
-Authors: D. Laurí and B. Lennox
-Journal: Chemometrics and Intelligent Laboratory Systems
-Year: 2014

Cita come

David Laurí (2025). Extended Partial Least Squares (https://it.mathworks.com/matlabcentral/fileexchange/44345-extended-partial-least-squares), MATLAB Central File Exchange. Recuperato .

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Versione Pubblicato Note della release
1.1.0.0

The paper that describes the algorithm has been accepted an published, then the reference to that paper has been updated.
1.0.0.0