Description: Even the best algorithms are only effective if they are trained on appropriate data. This article discusses common pitfalls in creating a training data set.

Description: Health care predictive analytics varies between payers and providers as well as being a powerful tool in business decision modeling.

Description: In this article, we will overview some popular tree-based models and understand how such models may be applied to the insurance industry.

Description: The article explores the possibility of using the emerging technology for life insurers to build a monitor system for better risk and profitability management.

Description: Looks at free and inexpensive resources for the novice in predictive analytics, covering the data analysis theory as well as the most commonly used languages/software used in the field.

Description: It talks about the major areas of data science and how to learn data science with the actuarial background.

Description: Second article in a series on how to use predictive analytics to improve the development of long-term care projection assumptions.

Description: Abstracts of recent articles of interest to health actuaries

Description: An introduction of predictive modeling techniques that are applicable to insurance industry, including generalized linear model (GLM) and classification and regression tree model(CART). Other models such as data clustering, neural network, and support vector machine (SVM), are also briefly discussed.