Description: This article gives a brief overview of ways to extend clustering analysis beyond basic methods such a k-means

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 artcle looks at the most important features necessary to conduct a meaningful quantitative analysis. The article also discusses how predictive analytics should be used as a tactic to anwer question and not an end in of itself.

Description: Describes goals of the section for the coming year.

Description: Summary of what the section has accomplished over the past year.

Description: Overview of regularization and least angle regression approaches.

Description: A look into how machine learning models implement classification and regression at a deeper level. Covers topics such as multi-regression, softmax, and ROC charts.

Description: Evaluates the ability of various model types to automatically approximate various mathematical formulas. This can be used as a guide for feature engineering.

Description: This article is a basic introduction to information theory with the goal of explaining the maximal information coefficient.

Description: Description of SOA's initiative in predictive analytics