Decision tree algorithm is a kind of data mining model to make induction learning algorithm based on examples. It is easy to extract display rule, has smaller computation amount, and could display ...

A decision tree can be constructed by using various algorithms, such as ID3, C4.5, or CART, that aim to find the optimal split at each node based on some criteria, such as entropy, information ...

Decision trees are a type of data mining algorithm that build a hierarchical structure of rules or conditions to classify or predict the outcome of a data point.

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 ...

Decision tree-based algorithms serve as the fundamental step in application of the decision tree method, which is a predictive modeling technique for classification of data. This chapter provides a ...

Decision tree data mining techniques perform four important functions. Decision trees: 1. Operate as a form of exploration tool on geological field data collected and stored in a database; ...

Based on the purity deviation difference and direction deviation, the segmentation values in data label classification are reconstructed and the decision tree structure layer is reorganized. The ...