What is it about?

Do you need to discover significant relationships from a data set containing > 10 variables? Then worth reading this. This is a mini-review of recent advancement in statistical modeling that couples with machine learning algorithms. It shows a new era for data analysis.

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Why is it important?

The concept is important because it bridges between statistics (hypothesis-testing) and machine learning (information-driven). Those who normally use statistics for data analysis are recommended to read this, aiming at learning non-linear, non-additive statistical approaches.

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This page is a summary of: Statistically reinforced machine learning for nonlinear patterns and variable interactions, Ecosphere, November 2017, Wiley,
DOI: 10.1002/ecs2.1976.
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