Titlebook: Decision Trees with Hypotheses; Mohammad Azad,Igor Chikalov,Beata Zielosko Book 2022 The Editor(s) (if applicable) and The Author(s), unde

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书目名称Decision Trees with Hypotheses网络公开度学科排名




书目名称Decision Trees with Hypotheses被引频次




书目名称Decision Trees with Hypotheses被引频次学科排名




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书目名称Decision Trees with Hypotheses年度引用学科排名




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书目名称Decision Trees with Hypotheses读者反馈学科排名

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Building Better Input RepresentationsIn this chapter, we consider main notions for Part I: decision tables and uncertainty measures, decision trees, and decision rules derived from decision trees.

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Introduction,In this chapter, we discuss main goals of the book, two its parts, prospects of using decision trees with hypotheses, and the use of book.

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Mohammad Azad,Igor Chikalov,Beata ZieloskoPresents the concept of a hypothesis about the values of all attributes.Provides tools for the experimental and theoretical study of decision trees with hypotheses.Compares these decision trees with c

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进入

Dynamic Programming Algorithms for Minimization of Decision Tree Complexitycomputer experiments on various data sets from the UCI ML Repository and randomly generated Boolean functions. Decision trees with hypotheses, generally, have less complexity than conventional decision trees, i.e., they are more understandable and more suitable as a means for knowledge representation.

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Greedy Algorithms for Construction of Decision Trees with Hypotheses the results of computer experiments on various data sets and randomly generated Boolean functions. We also study the length and coverage of decision rules derived from the decision trees constructed by greedy algorithms.