Description: Read the December 2018 issue of Predictive Analytics and Futurism published by the Predictive Analytics and Futurism Section.

Description: Feature article discussing the usefulness of Lorenz and Lift curves.

Description: Chairperson's column for the May 2019 issue of Predictive Analytics & Futurism.

Description: A review of the Johns Hopkins Data Science Specialization courses with special emphasis on how they may be useful to actuaries.

Description: An autobiographical journey from actuarial student to data scientist.

Description: This article discusses how to handle semisupervised data. This type of data might have a large number of observations, yet a small number of labels.

Description: An introduction to the methods and parameters for Bayesian Hyperparameter Optimization in a Life Insurance context.

Description: In this article we examine the benefits and drawbacks of using a global surrogate of a black-box model. Are surrogates a comfortable middle ground that provide insurers high predictive power as well as model explainability?

Description: In How Significant Is Statistical Significance? The author discusses the p-value that is often used to determine significance. Sometimes we place too much reliance upon canned metrics and lose the ability to notice when something is mathematically sound but not sensible. The article provides three simple examples that require no complicated mathematics to follow yet provide a basis for some deep thought about statistical significance versus substantive significance.

Description: A discussion on how the look of charts and graphs can affect comprehension of data.