It is possible to post-process decision tree prediction rules to remove unnecessary duplication of predictor variables, but the demo program, and most machine learning library implementations, do not ...

Overview Understanding key machine learning algorithms is crucial for solving real-world data problems effectively.Data ...

"Clinical decision support systems, for example, are designed to help practitioners stay up to date on new developments without requiring them to spend their entire day reading the medical literature.

Recent scientific article explores the use of machine learning techniques to identify the key risk factors associated with ...

This case study evaluates modelling relationships between the combination of decision variables and uncertain factors. There are 6 uncertain factors that influence water quality varying within a ...

Compared to other regression techniques, decision tree regression is easy to tune, works well with small datasets and produces highly interpretable predictions. However, decision tree regression is ...