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Modeling Decisions for Artificial Intelligence

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Cover of 'Modeling Decisions for Artificial Intelligence'

Table of Contents

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    Book Overview
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    Chapter 1 Provenance and Privacy
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    Chapter 2 Comparison of Risk Averse Utility Functions on Two-Dimensional Regions
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    Chapter 3 Symmetrization Methods for Aggregation Functions
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    Chapter 4 Event-Based Transformations of Capacities
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    Chapter 5 Pan-Integrals Based on Optimal Measures
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    Chapter 6 Orness and Cardinality Indices for Averaging Inclusion-Exclusion Integrals
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    Chapter 7 $$L_1$$ -space for Sugeno Integral
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    Chapter 8 An Adaptation of the ML-kNN Algorithm to Predict the Number of Classes in Hierarchical Multi-label Classification
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    Chapter 9 On Fuzzy Clustering for Categorical Multivariate Data Induced by Polya Mixture Models
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    Chapter 10 Comparison of Fuzzy Co-clustering Methods in Collaborative Filtering-Based Recommender System
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    Chapter 11 Differentially Private Data Sets Based on Microaggregation and Record Perturbation
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    Chapter 12 A Methodology to Compare Anonymization Methods Regarding Their Risk-Utility Trade-off
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    Chapter 13 Session-Based Network Intrusion Detection Using a Deep Learning Architecture
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    Chapter 14 A Hybrid Model of ARIMA and ANN with Discrete Wavelet Transform for Time Series Forecasting
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    Chapter 15 A Novel Hybrid Model for Activity Recognition
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    Chapter 16 Constructing Document Vectors Using Kernel Density Estimates
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    Chapter 17 On Cell Detection System with User Interaction
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    Chapter 18 A Fuzzy Colour Model Sensitive to the Context: Study Cases Using PRAGR and Logics
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    Chapter 19 Joint Subjective Opinions
Attention for Chapter 8: An Adaptation of the ML-kNN Algorithm to Predict the Number of Classes in Hierarchical Multi-label Classification
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Citations

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Chapter title
An Adaptation of the ML-kNN Algorithm to Predict the Number of Classes in Hierarchical Multi-label Classification
Chapter number 8
Book title
Modeling Decisions for Artificial Intelligence
Published by
Springer, Cham, October 2017
DOI 10.1007/978-3-319-67422-3_8
Book ISBNs
978-3-31-967421-6, 978-3-31-967422-3
Authors

Thissiany Beatriz Almeida, Helyane Bronoski Borges

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 25%
Professor 1 13%
Researcher 1 13%
Student > Bachelor 1 13%
Unknown 3 38%
Readers by discipline Count As %
Computer Science 4 50%
Unknown 4 50%

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