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JORGE ÁLVAREZ LLERAS

Average Time Complexity of Decision Trees [electronic resource] / by Igor Chikalov.

Por: Colaborador(es): Tipo de material: TextoSeries Intelligent Systems Reference Library | ; -21Descripción: XII, 104p. 6 illus. online resourceISBN:
  • 9783642226618 99783642226618
Tema(s): Clasificación CDD:
  • 006.3 223
Recursos en línea:
Contenidos:
1 Introduction -- 2 Bounds on Average Time Complexity of Decision Trees -- 3 Representing Boolean Functions by Decision Trees -- 4 Algorithms for Decision Tree Construction -- 5 Problems Over Information Systems.
Resumen: Decision tree is a widely used form of representing algorithms and knowledge. Compact data models and fast algorithms require optimization of tree complexity. This book is a research monograph on average time complexity of decision trees. It generalizes several known results and considers a number of new problems.The book contains exact and approximate algorithms for decision tree optimization, and bounds on minimum average timeá complexity of decision trees. Methods of combinatorics, probability theory and complexity theory are used in the proofs asá well as concepts from various branches of discrete mathematics and computer science.áThe considered applications include the study of average depth of decision trees for Boolean functions from closed classes, the comparison of results of the performance of greedy heuristics for average depth minimization with optimal decision trees constructed by dynamic programming algorithm, and optimization of decision trees for the corner point recognition problem from computer vision. The book can be interesting for researchers working on time complexity of algorithms and specialists in test theory, rough set theory, logical analysis of data and machine learning.
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1 Introduction -- 2 Bounds on Average Time Complexity of Decision Trees -- 3 Representing Boolean Functions by Decision Trees -- 4 Algorithms for Decision Tree Construction -- 5 Problems Over Information Systems.

Decision tree is a widely used form of representing algorithms and knowledge. Compact data models and fast algorithms require optimization of tree complexity. This book is a research monograph on average time complexity of decision trees. It generalizes several known results and considers a number of new problems.The book contains exact and approximate algorithms for decision tree optimization, and bounds on minimum average timeá complexity of decision trees. Methods of combinatorics, probability theory and complexity theory are used in the proofs asá well as concepts from various branches of discrete mathematics and computer science.áThe considered applications include the study of average depth of decision trees for Boolean functions from closed classes, the comparison of results of the performance of greedy heuristics for average depth minimization with optimal decision trees constructed by dynamic programming algorithm, and optimization of decision trees for the corner point recognition problem from computer vision. The book can be interesting for researchers working on time complexity of algorithms and specialists in test theory, rough set theory, logical analysis of data and machine learning.

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BIBLIOTECA

JORGE ÁLVAREZ LLERAS
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