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Saturday, April 08, 2017

Adaptive Machine Learning

Good points in DSC article below on adaptive machine learning.    I often make the case that you should often consider if your modeling should be modeled adaptively.    Data and context can be changing even if we don't expect it.  Time often drives change.  Even if your data is not necessarily streaming.  With an eye towards risk and change management:

Adaptive Machine Learning

Posted by PG Madhavan on May 20, 2016 at 5:30amView Blog
Machine Learning today tends to be “open-loop” – collect tons of data offline, process them in batches and generate insights for eventual action. There is an emerging category of ML business use cases that are called “In-Stream Analytics (ISA)”. Here, the data is processed as soon as it arrives and insights are generated quickly. However, action may be taken offline and the effects of the actions are not immediately incorporated back into the learning process. If we did, it is an example of a “closed-loop” system – we will call this approach “Adaptive Machine Learning” or AML. ISA is a precursor to AML.  .... " 

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