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Quick guide to PLS
Use [Alt-Tab] to go to LatentiX (if running)
Press [Page Down] or [Enter] to continue
Press [ESC] to end the show
2
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