Need to do a JMP Pro demo next week for a customer interested in PLS with categorical (binomial) response. Does anyone have a good dataset to demo this? All the PLS datasets I've found so far involve numeric responses.
Thanks,
Mark
In the attached zip file is a journal comparing PCA and PLS . Within there is an Amour tiger data set having a categorical response.
There is some description involved and some other examples too. I guess this should help with what you are looking for. You have to check if all works in JMP 15 as I have it not checked.since some time
Hi Mark,
Just adding an example that I have used from a science/engineering industry situation.
This is from a forensic analytical chemistry lab. The company's branded products are sold all over the world. Sometimes counterfit product is sold as their's. When they have customer complaints they need to establish quickly if it is their product or a counterfit. Traditionally this is done by testing a sample with many different chemical tests over days. This costs a lot in lab time and means customer problems take too long to be resolved.
The solution is to use data analytics on a fast chemical analysis that generates a lot of data.
In the attached, the RT columns represent the peak area at different retention times from chromatograms. Each peak is a different chemical entity. And the area is proportional to the amount of that entity in the sample.
I show how different visual and modelling techniques allow you to understand the differences between the 3 sources and how you could determine what the source is for an unknown. PLS would be one of the options.
Hope that helps.
Phil
Please remember to mention the excellent book about PLS using JMP by Mia and Ian!
Curious if someone can help me with explaining the applications for PLS vs. Gen Reg (with validation)? Why would one use PLS over Gen Reg? Or vice versa?
Any of the example discriminant analysis datasets in the sample library would also work.
The "Owl Diet" dataset is simple to understand and work through the concepts of PLS-DA.
Thank you all, very helpful! The customer (NeuroVision) is also asking if it's possible to get a ROC diagnostic curve from PLS? Seems like it's not an option, but is there a round about way to do it and also what is the reasoning why it is not an option for PLS w/ categorical responses? Apparently they are using Python to get this type of a result and would like JMP Pro to do something similar.
Well of course you can do it in Python because it is a programming language. By the same token, you can do it in JMP via scripting. Okay, now that I have gotten my "snarkiness" out of the way...
I was hoping that you could save the prediction formula from PLS-DA and get the ROC curve through the Model Comparison platform. Unfortunately, it looks like the format for the PLS-DA prediction formula does not work well with the Model Comparison platform. It looks like the ROC curve would need to be built via scripting.
Just another opinion: I know ROC curves are a nice way to compare models. However for binomial responses I like to look more at the misclassification rates and especially how homogeneous the errors are distributed to error 1 vs error 2. Why? a model which predicts one level perfectly and the other almost because of more or less rare events it might still look better than another model looking at the ROC curve alone, I believe (@statisticians, please correct me if I'm wrong, am just a mathematician ).
That said you result in a model which just says all predictions are resulting in one level and gets only some error 1 predictions. There might be a model which predicts more errors in an absolute sense but they are predicting both levels kind of good. This model might be not as good as the other model from an ROC curve or as well the pure misclassification rate, but I would still choose it because it is probably closer to the reality.
Update to this thread. I've noticed an issue with PLS when modeling categorical responses where the prediction formula saved to the datatable does not have the Response Probability column property. As a result, it is not possible to compare the PLS model with other classification models in Model Comparison. There may be a specific reason for this, but I am not yet aware what it might be. I'll update this thread with what I learn from Technical Support regarding this issue.
