In this study, we attempt to leverage the ability of supervised learning methods, such as ANNs, KANs, and gradient-boosted decision trees, to approximate complex multivariate functions in order to ...

allowing users to assemble algorithms from algorithm building blocks. This paper provides a comparison between students' acceptance of both black-box and white-box decision tree algorithms. For these ...

Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining; it is the science of exploring large and complex bodies of data in order to discover ...

This is the first comprehensive book dedicated entirely to the field of decision trees in data mining and covers all aspects of this important technique. Decision trees have become one of the most ...

Obviously many algorithms need a definition of features to look at or a biggish training set of data to derive the solution from. This curated list comprises awesome libraries, data sources, tutorials ...

Researchers compare advanced genetic methods that pinpoint a tree’s origin on a continuous scale, refining seed sourcing, ...