A decision tree is a machine learning technique that can be used for binary classification or multi-class classification. A binary classification problem is one where the goal is to predict the value ...

The visual data mining process, seen in the first part of this two-part article, revealed patterns in four dimensions between cumulative gas well production and independent variables ...

The system is structured around a client-server architecture designed to provide scalability, remote accessibility, and robust data security. On the client side, a lightweight graphical application ...

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 ...

Missing values may be easier to manage with decision trees than they are with other classification methods. 33 The tree-building algorithm in the Salford System CART software uses a method of ...

An innovative algorithm called Spectral Expansion Tree Search helps autonomous robotic systems make optimal choices on the move.

But there is also some empirical work comparing various algorithms across many datasets and drawing some conclusions, what types of problems tend to do better with trees vs logistic regression.

The authors’ approach is based on differences between assembly op-code frequencies in malware and benign classes. They have also utilized decision tree algorithms to simplify the classification.