A new Alchemite™ feature is ‘making it real’ for scientists and engineers trying to understand processes such as formulation, materials production, or manufacturing. Watch the explainer video to see multi-stage modelling in action.
Throw some data at a tool such as Alchemite™ and it will quickly tell you how the inputs to your system drive the outputs and then use that information to make predictions that help you to optimize your outcomes. But some of the subtlety of real, complex processes can be lost in such studies if they treat all of the inputs and outputs the same. Real processes are often multi-stage in nature. Some of the inputs are only relevant to parts of the overall process. And we may want to understand and control not simply the final outputs, but also what happens at intermediate points.
The new Multi-Stage Modelling feature in Alchemite™, developed in response to user feedback, enables you to do just that. You can quickly specify the different steps in a multi-stage process and then train a machine learning model that accounts for this complexity, delivering more precise predictions and a more complete analysis of the system being studied.
