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 ...

What are the advantages of logistic regression over decision trees? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better ...

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.

Decision Trees for Decision-Making Here is a [recently developed] tool for analyzing the choices, risks, objectives, monetary gains, and information needs involved in complex management decisions ...

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 ...

Decision trees, regression, and neural networks all are types of predictive models. People often confuse predictive analytics with machine learning even though the two are different disciplines.

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of decision tree regression using the C# language. Unlike most implementations, this one does not use recursion ...