Bayesian Optimization

Drive faster, more efficient innovation with the latest in intelligent experimentation

Innovate faster with less

Begin with small experiments, use data from earlier studies, and iteratively refine your search for the best factor settings as goals are met.

Learn with ease, see quick results

Make fewer assumptions and fewer mistakes with a streamlined, integrated modeling and data augmentation approach.

Reduce startup cost

Not every experiment needs to start from scratch. Achieve your goals faster by using historical data or salvaging a previous DOE.

Bayesian Optimization accelerates industrial R&D and lowers the barrier to entry, saving time and resources by learning from observed response values while using the project goals to recommend the settings to test next.
JMP
Christopher Gotwalt, Senior Director, Advanced Analytics R&D

All the power. None of the complexity.

Extend the value of JMP to solve bigger and more challenging analytic problems with the latest data science techniques, including predictive modeling and machine learning.

Buy JMP Pro now

Bayesian Optimization platform in JMP

The Profiler: More than model visualization and optimization

Working directly with the Profiler and improved algorithms for fitting Gaussian process models, Bayesian Optimization has eliminated much of the cumbersome statistical machinery that gets between the experimenter and the solution, while at the same time filling in institutional knowledge gaps.

Goal-directed augmentation

With as few as two starting experimental runs, Bayesian Optimization can suggest the best next run to maximize the information gained from every experimental dollar. Whether you have historical data or are beginning from scratch, you can learn quickly.

Next best run suggestions in Bayesian Optimization platform
Bayesian optimization

High stakes data advantage

In high process and product innovation industries with rapid learning cycles, Bayesian Optimization is impactful, significantly reducing the time and resources needed for experimental design.

Rapid learning from both response and run

Bayesian Optimization learns from the responses with each iteration and gives the experimenter more precise guidance than traditional approaches on when they can stop experimenting.

Bayesian Optimization platform in JMP

All the power. None of the complexity.

Extend the value of JMP to solve bigger and more challenging analytic problems with the latest data science techniques, including predictive modeling and machine learning.

Buy JMP Pro now

JMP® Pro

All the power. None of the complexity.

Extend the value of JMP to solve bigger and more challenging analytic problems with the latest data science techniques, including predictive modeling and machine learning. Harness the power of best-in-class analysis performance while maintaining the flexibility of desktop software.

Learn more

JMP Pro

All the power. None of the complexity.

Extend the value of JMP to solve bigger and more challenging analytic problems with the latest data science techniques, including predictive modeling and machine learning.

Buy JMP Pro now