Oct 29, 2024 · Several algorithms are available for building decision trees, each with its unique approach to splitting nodes and managing complexity. The most commonly used algorithms …

Jan 30, 2025 · Tree-based algorithms are a fundamental component of machine learning, offering intuitive decision-making processes akin to human reasoning. These algorithms construct …

Nov 2, 2022 · Though Decision Trees look simple and intuitive, there is nothing very simple about how the algorithm goes about the process deciding on splits and how tree pruning occurs. In …

In computational complexity theory, the decision tree model is the model of computation in which an algorithm can be considered to be a decision tree, i.e. a sequence of queries or tests that …

Jan 16, 2025 · Decision tree is a simple diagram that shows different choices and their possible results helping you make decisions easily. This article is all about what decision trees are, how …

Decision tree algorithms can be considered as iterative, top-down construction method for the hypothesis (classi er). You can picture a decision tree as a hierarchy of deci-sions, which are …

In this paper, we theoretically and experimentally study and compare the computational power of the most common classi- cal top-down decision tree algorithms (C4.5 and CART).

Nov 16, 2018 · The goal of this paper is to theoretically and experimentally analyse and compare the complexity of decision tree algorithm for classification task. The decision tree classifiers …

Mar 5, 2025 · We present a comprehensive classical and parameterized complexity analysis of decision tree pruning operations, extending recent research on the complexity of learning …

The decision tree complexity of a function is the number of bits examined by the most efficient decision tree on the worst case input to that tree. We are now ready to consider several …