Patients are less comfortable with predictive models used for health care administration compared with those used in clinical practice, signaling misalignment between patient comfort, policy, and ...

As predictive models proliferate, providers and decision makers require accessible information to guide their use. Preventing and combating bias must also be priorities in model development and in ...

Inaccurate or overlooked alerts on manufacturing data can be reduced with proper data handling when developing and deploying predictive models. Data analytics, and specifically predictive analytics, ...

CEO of InfluxData, a leading time series platform, board member for One Heart Worldwide and board advisor for Lucidworks and The Fabric. In the current global business landscape, data-driven ...

Models are important for understanding the current and future states of the world and we use many, for instance the capital asset pricing model, to help us understand markets and investing. But most ...

This course covers nonparametric modeling of complex, nonlinear predictive relationships between variables. Covered supervised learning methods include neural networks, trees, nearest neighbors, local ...