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Prescriptive Analytics
This extension offers an operator to do prescriptive optimization. This means you vary the values of an example to optimize a custom fitness function which may derive from a model. Currently supported optimizers: - Grid - Evolutionary - BYOBA
Version 0.2.0
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- changing java version to 11+ by changing the rapidminer-extension version to 1.0.7
- changing minimum version to 10.0.0
- Adding a new port "optimization history" to the prescriptive optimization operator, which contains the result of every iteration of the optimization.
Version 0.16
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- Added proper error messages if the start value is out of bounds
- The error messages of the inner processes are now properly shown in the GUI.
Version 0.1.5
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- Added an option to add get candidate results. I.e. more than just the best solution
- Evolutionary is now correctly using custom random seeds - Added Powell as an unbounded optimization method
- A lot of code improvement for optimizer creation and parameter handling
Version 0.1.4
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- Added "random", "input example" and "reference example" as a starting point options.
- Removed the start setting in SimpleBounds. Please provide start values via input/reference exa. E.g. via Set Data.
- Added a few better error messages for missing references, missing bounds etc
Version 0.1.3
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- Added a number of interpolation point default boolean for BYOBA
- Added CMA-ES as a optimization method
Product Details
| Version | 0.2.0 |
| File size | 774 kB |
| Downloads | 16625 (47 Today) |
| Vendor | RapidMiner Labs |
| Category | Machine Learning |
| Released | 9/26/25 |
| Last Update | 9/26/25 11:15 AM |
| License | AGPL |
| Product web site | rapidminer.com |
| Rating |

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