Decision trees are flexible enough to handle items with a mixture of real-valued and categorical features, as well as items with some missing features. They are expressive enough to model many ...

You will have the opportunity to apply Neural Networks to classify or predict outcomes in a given dataset and evaluate model performance in the labs for this module. This module will focus on the ...

The tutors of this course have been at the forefront of developing R models and tools for economic evaluation. This course aims to teach the use of R for building decision trees, Markov, and ...

Objective The objective was to examine the 22 variables from the Sport Concussion Assessment Tool’s 5 th Edition (SCAT5) Symptom Evaluation using a decision tree analysis to identify those most likely ...

These tools include pre-mortem analysis, scenario analysis, decision trees, models of wisdom of the crowd and informational cascades. This course introduces fundamental concepts and modeling tools for ...

In the issue’s second paper, “Financial distress prediction with optimal decision trees based on the optimal sampling probability”, Guotai Chi, Cun Li, Ying Zhou and Taotao Li develop a tree-based ...