This paper presents a survey of evolutionary algorithms that are designed for decision-tree
induction. In this context, most of the paper focuses on approaches that evolve decision …

The induction of decision trees is a widely-used approach to build classification models that
guarantee high performance and expressiveness. Since a recursive-partitioning strategy …

Classification is a frequently encountered data mining problem. Decision tree techniques
have been widely used to build classification models as such models closely resemble …

Tree-based classifiers are important in pattern recognition and have been well studied.
Although the problem of finding an optimal decision tree has received attention, it is a hard …

Despite the large overall beneficial effects of endovascular treatment in patients with acute
ischemic stroke, severe disability or death still occurs in almost one-third of patients. These …

This paper addresses a data mining task of classifying data stream with concept drift. The
proposed algorithm, named Concept-adapting Evolutionary Algorithm For Decision Tree …

Decision trees are widely disseminated as an effective solution for classification tasks.
Decision tree induction algorithms have some limitations though, due to the typical strategy …

Machine learning applications related to high-stakes decisions are often surrounded by
significant amounts of controversy. This has led to increasing interest in interpretable …

Among the several tasks that evolutionary algorithms have successfully employed, the
induction of classification rules and decision trees has been shown to be a relevant …

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