Outlier Management - Detection and Correction
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- čas přidán 13. 07. 2024
- If you want to learn more about outlier management:
- towardsdatascience.com/forecasting-how-to-detect-outliers-cb65faafcd97
- medium.com/@nicolas-vandeput/outlier-detection-and-correction-694f9f474c2d
Want to learn more about demand forecasting and inventory optimization?
www.amazon.com/stores/Nicolas... - Věda a technologie
Hi I am an S&OP manager based in Pakistan, I wanted to know how can I get access to your book? also I have been working to create baseline forecast in my organization but since there are no historic demand driver details available its very difficult to generate baseline forecast, any mathematical approach that I can use to atleast begin with forecasting for longer period of months?
Thank you for posting these webinars. Even with all the Q&A on shortages I'm still confused on figuring out unconstrained demand. On your slide you say to bypass it, but in your book it says to censor it. Are you meaning the same thing for both the slide and book? Also, on the slide in this webinar, that's also book, it looks like you're using a default value for demand, which looks to be the last demand value before the shortage for the duration of the shortage. Is that what you use?
Your book mentions forecasting techniques that might help estimate unconstrained demand, but I can't find any examples. Can you share those techniques? Do you use machine learning techniques, or an equation?
Thanks!
I usually don't use equations to clean shortages. Nowadays, I just censor them.
nicolas-vandeput.medium.com/forecasting-demand-despite-shortages-fee899120c08
Thank you for your webinar. I have a question regarding outliers. I am conducting a serum biomarker research (medical research) consisting 50 patients vs. 50 controls. I have 3 cases having non-detectable values (above the detection level) in the same group. This group is already have higher levels than the other one. I do not want to remove those cases and lose the data. Which strategy should I use ? Should I imputate them with the mean value of the relevant group? or Should I enter the measured highest value/s instead of undetectable ones ? or else ? Thank you in advanced.
Hello, sorry I specialize in supply chain demand planning - I don't think I am legitimate or have the experience required to advise you regarding how to conduct medical research. All the best!
Hi Nicolas, it is a very explanatory webinar about outliers. I have a question. Do we need to apply outlier detection process based on train data, or whole data (train+test)? I hope my question is clear.
I would try not to do any statistical outlier detection. I would invest more in data cleaning. If you remove outliers from the test set, you are somehow overfitting - so I would not do it.