Decision trees are useful for relatively small datasets that have a relatively simple underlying structure, and when the trained model must be easily interpretable, explains Dr. James McCaffrey of ...

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. "Jump ...

For better accountability, we should shift the focus from the design of these systems to their impact. Describing a decision-making system as an “algorithm” is often a way to deflect accountability ...

The cotton bollworm, Helicoverpa armigera (Hϋbner) is one of the most important pests affecting crop production globally. The data-mining technique, for predicting pest incidence using biotic and ...

Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic terms, ...

Computer scientists often encounter problems relevant to real-life scenarios. For instance, "multiagent problems," a category characterized by multi-stage decision-making by multiple decision makers ...

An innovative algorithm called Spectral Expansion Tree Search helps autonomous robotic systems make optimal choices on the move. In 2018, Google DeepMind's AlphaZero program taught itself the games of ...