Implementing decision tree regression from scratch is not simple, but by doing so you can modify the system to handle unusual problem scenarios, and you can easily integrate the prediction system into ...

If the signal to noise ratio is low (it is a ‘hard’ problem) logistic regression is likely to perform best. In technical terms, if the AUC of the best model is below 0.8, logistic very clearly ...

Decision trees are a simple but powerful prediction method. Figure 1: A classification decision tree is built by partitioning the predictor variable to reduce class mixing at each split. Figure 2 ...

For more information on this research see: Comparison and Analysis of the Effectiveness of Linear Regression, Decision Tree, and Random Forest Models for Health Insurance Premium Forecasting.

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 ...

Implementing decision tree regression from scratch is not simple, but by doing so you can modify the system to handle unusual problem scenarios, and you can easily integrate the prediction system into ...