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

Intersect

Decision Trees with Hypotheses for Recognition of Monotone Boolean Functions and for Sortingt elements from linearly ordered set, .. For each of these problems, we compare the complexity of five types of optimal (relative to the depth or the number of realizable nodes) decision trees. We also study the complexity of decision trees constructed by greedy algorithms and analyze the length of decision rules derived from these trees.

集聚成团

储备

平淡而无味

https://doi.org/10.1007/978-3-030-36721-3 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.

RADE

惩罚

https://doi.org/10.1007/978-3-030-36721-3 which consists of an infinite set of elements and an infinite set of two-valued functions (attributes) defined on the set of elements. We consider the notion of a problem over information system, which is described by a finite number of attributes: for a given element, we should recognize values of

expound

https://doi.org/10.1007/978-3-030-14524-8 which consists of an infinite set of elements and an infinite set of two-valued functions (attributes) defined on the set of elements. We consider the notion of a problem over information system, which is described by a finite number of attributes: for a given element, we should recognize values of

纹章

Kamilya Smagulova,Alex Pappachen James consists of an infinite set of elements and an infinite set of subsets of this set called concepts. We consider the notion of a problem over a family of concepts that is described by a finite number of elements: for a given concept, we should recognize which of the elements under consideration belo

高尔夫

填满

Deep Learning Approaches to Text Productioncomputer 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.