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Advances in Machine Learning II

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Cover of 'Advances in Machine Learning II'

Table of Contents

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    Book Overview
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    Chapter 1 Knowledge-Oriented and Distributed Unsupervised Learning for Concept Elicitation
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    Chapter 2 Toward Interactive Computations: A Rough-Granular Approach
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    Chapter 3 Data Privacy: From Technology to Economics
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    Chapter 4 Adapting to Human Gamers Using Coevolution
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    Chapter 5 Wisdom of Crowds in the Prisoner’s Dilemma Context
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    Chapter 6 Towards Multistrategic Statistical Relational Learning
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    Chapter 7 About Knowledge and Inference in Logical and Relational Learning
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    Chapter 8 Two Examples of Computational Creativity: ILP Multiple Predicate Synthesis and the ‘Assets’ in Theorem Proving
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    Chapter 9 Logical Aspects of the Measures of Interestingness of Association Rules
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    Chapter 10 Clustering the Web 2.0
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    Chapter 11 Induction in Multi-Label Text Classification Domains
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    Chapter 12 Cluster-Lift Method for Mapping Research Activities over a Concept Tree
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    Chapter 13 On Concise Representations of Frequent Patterns Admitting Negation
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    Chapter 14 A System to Detect Inconsistencies between a Domain Expert’s Different Perspectives on (Classification) Tasks
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    Chapter 15 Advances in Machine Learning II
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    Chapter 16 Simple Algorithms for Frequent Item Set Mining
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    Chapter 17 Monte Carlo Feature Selection and Interdependency Discovery in Supervised Classification
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    Chapter 18 Machine Learning Methods in Automatic Image Annotation
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    Chapter 19 Integrative Probabilistic Evolving Spiking Neural Networks Utilising Quantum Inspired Evolutionary Algorithm: A Computational Framework
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    Chapter 20 Machine Learning in Vector Models of Neural Networks
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    Chapter 21 Nature Inspired Multi-Swarm Heuristics for Multi-Knowledge Extraction
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    Chapter 22 Discovering Data Structures Using Meta-learning, Visualization and Constructive Neural Networks
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    Chapter 23 Neural Network and Artificial Immune Systems for Malware and Network Intrusion Detection
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    Chapter 24 Immunocomputing for Speaker Recognition
Attention for Chapter 16: Simple Algorithms for Frequent Item Set Mining
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Citations

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33 Mendeley
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Chapter title
Simple Algorithms for Frequent Item Set Mining
Chapter number 16
Book title
Advances in Machine Learning II
Published by
Springer, Berlin, Heidelberg, January 2010
DOI 10.1007/978-3-642-05179-1_16
Book ISBNs
978-3-64-205178-4, 978-3-64-205179-1
Authors

Christian Borgelt, Borgelt, Christian

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Iran, Islamic Republic of 1 3%
Indonesia 1 3%
United States 1 3%
Germany 1 3%
Unknown 29 88%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 30%
Student > Ph. D. Student 7 21%
Researcher 4 12%
Student > Bachelor 3 9%
Student > Doctoral Student 2 6%
Other 5 15%
Unknown 2 6%
Readers by discipline Count As %
Computer Science 24 73%
Engineering 2 6%
Agricultural and Biological Sciences 1 3%
Social Sciences 1 3%
Business, Management and Accounting 1 3%
Other 0 0%
Unknown 4 12%