Quick guide to PLS

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Dioxin and fatty acid data

• Problem

To develop a PLS model that can predict the dioxin concentration (y) in ng/(kg fat) in fish meal samples from fatty acids profiles (X).

In total 64 samples were analysed and gas chromatography was used for the determination of 32 fatty acids (including an unidentified group). The results are given in % of all 32 fatty acids.

The very expensive and complex dioxin analyses were performed by a German laboratory.

• Data

The dimension of the data structure is 64 objects x 34 variables.

The first two variables are the species code (herring, sprat, blue whiting, sand eel etc. in total 15 species) and the dioxin content.

Variables 3 to 34 are the chromatographic variables.

Source: Rapid dioxin assessment in fish products by fatty acid pattern recognition, Marc Bassompierre, Lars Munck, Rasmus Bro and Søren Balling Engelsen, Analyst, 129, 553-558, 2004.

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Get the data

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The data in the WorkBench

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Select the fatty acid variables

Write 3:34 and press [ENTER] or selectthe fatty acid variables in the Variables listbox

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Define a variable set

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Give the set a name, e.g. X

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Now select dioxin in the listbox

The plot window always show the actual selection inthe Objects and Variables listboxes

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Plot dioxin as a function of the objects

Click on this icon

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Define a variable set containing only the dioxin variable

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Give the set a name, e.g. y

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Autoscale the X data

First select X in the Sets box

Then select autoscale

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The effect is shown instantly in the plot

Click Transform to see how the transformationaffects the data

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Make a PLS model

Select PLS in the dropdown menu

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Select the dependent variable(s)

First select y in the Sets box

Then select y (or click on Dioxin in the listbox)

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Autoscale y

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Choose cross validation

Select CV: Syst123 (Venetian blinds)

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Choose the number of segments

In this case we use eight segments

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Calculate the PLS model

Press Calculate

Then press OK

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Plot the error

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RMSEC & RMSECV

Select both using CTRL

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U vs T plot

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U vs T plot

Change the markers & labels

TIP: use the arrows keys to change the number of components

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Plot regression coefficicents

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Regression coefficients

Change the markers & labels

TIP: use the arrows keys to change the number of components

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Plot Actual vs Predicted

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Actual vs Predicted for six components

Change the markers & labels

TIP: use the arrows keys to change the number of components

THE END