Part 2: Should we Send the Azure Machine Learning Model to Market?

The previous post concentrated on deciding if a categorical Machine Learning model should be released for production or not. This post concentrates on interpreting the scores of a regression model and the implication in using it in a decision management feature. Decision management solutions apply business rules written by humans and automatically apply them to the cases they are presented. Digital masters are more likely to include the output from a machine learning prediction into their decision management systems than those who are just starting their digital journey. For example, before machine learning was included, the rules might be: If the last inspection was 30 days ago then put the battery on the “inspection due” list. If there are more than 20 items on the “inspection due list” at a site…


Link to Full Article: Part 2: Should we Send the Azure Machine Learning Model to Market?

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