Description: This article describes a method that can be useful when re-fitting a risk score model to a population of only moderate size. Learn how to use concepts like ridge regression to train a model with partial credibility.

Description: This article compares three potential approaches to determining new coefficients for health-based risk scoring models: full recalibration, p-value credibility weighting, and penalized ridge regression.

Description: Specifies 6 rules which help shape not only good crime-scene analysis, but good futures practice, as well. These rules address project management and control.

Description: An introduction to Hidden Markov Models, which are used extensively in speech and facial recognition technology. They are a useful tool in forecasting time series and in developing categorizations of data based on the values of the data themselves.

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: The newer predictive modeling tools are powerful but they work best when supported by a lot of computing power. Parallel processing is very powerful but often very difficult to implement. Dihui and Richard take us through the maze of options with H2O, SparkNet/MLib and Mahout. Which do you use for a generalized linear model (GLM), and which is better for high-volume data manipulation?

Description: This article is about research studies that use the Delphi technique. It describes what a Delphi study is and gives a thumbnail sketch of two Delphi studies the Society of Actuaries has sponsored in the past 10 years, as well as a recently initiated Delphi study.

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: Reviewing a text covering multiple statistical modeling topics: e.g., generalized linear models, decision trees, clustering, using the statistical language R.