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Incremental Machine Learning with feeding data every hour?

I ran couple of simple ML examples available from the Documentation. A small data set with less than 100 records would take a whole 10 sec to be trained in my laptop. If I have a new set of sample data of 100 records available every hour, do I need to add those records to the population and train the entire Classifier all over again every hour? Is Classifier capable of retaining of its previous trained knowledge, while we keep feeding in newly available set of data to the Classifier every now & then?

POSTED BY: Teck Boon Lim
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Thanks I Van Veen, I just tried using the same approach of John's. It works well with a much shorter time in retraining. Wonderful!

POSTED BY: Teck Boon Lim
POSTED BY: Teck Boon Lim

On the site: https://medium.com/wolfram-events/multiparadigm-data-science-5-things-you-need-to-know-14ab75a15210 John McLoone explains the ML framework. In part 7 of the lecture at 3:25 minutes he shows that you can add data in a already trained network. https://youtu.be/JRW-BICsUG4?list=PLxn-kpJHbPx12mbdcVVWCelvcIL_R0X

POSTED BY: l van Veen
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