26 jun. 2018

Developing LOCAL calibrations with R

We can use also LOCAL in R with the Resemble package. I am testing the package these days with a set of petfood spectra (with protein reference values) imported from Win ISI with SNV and a second derivative math treatment. After, I select 65% for training and the rest for test.
 
The get predictions process of Resemble allow a configuration to check for the better number of sample or factors for the better prediction, so there are a lot of options and functions to check in this package.
 
This is a plot of the results for a standard configuration from the reference manual, that I would try to go more deep into, trying to find the best configuration.

ctrl <- mblControl(sm = "pls",
                   pcSelection = list("opc", 40),
                   valMethod = c("NNv"),
                   scaled = FALSE, center = TRUE)


ex1 <- mbl(Yr = Yr, Xr = Xr, Yu = NULL, Xu = Xu,
           mblCtrl = ctrl,
           distUsage = "predictors",
           k = seq(30, 150, 15),
           method = "wapls1",
           pls.c= c(7, 20))

Yu_anl<-getPredictions(ex1)


Clearly seems that some of the configurations have overfitting, but I am just starting to learn the package so more post will come up giving my progress with this package.

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