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Home > Advances in Data Analysis with Computational Intelligence Methods: Dedicated to Professor Jacek Żurada > Local Data Characteristics in Learning Classifiers from Imbalanced Data
Advances in Data Analysis with Computational Intelligence Methods: Dedicated to Professor Jacek Żurada |
Adam E Gawęda; Janusz Kacprzyk; Leszek Rutkowski; Gary G. Yen
Springer International Publishing
Advances in Data Analysis with Computational Intelligence Methods: Dedicated to Professor Jacek Żurada
Local Data Characteristics in Learning Classifiers from Imbalanced Data
Authors

Jerzy Błaszczyński; Jerzy Stefanowski

ARI Id

1665082131957_4749337

Access

Not Available Free

Pages

51-85

DOI

10.1007/978-3-319-67946-4_2

Chapter URL

https://rd.springer.com/chapter/10.1007/978-3-319-67946-4_2

Table of Contents of Book
Showing 1 to 20 of 24 entries
Chapters/HeadingsAuthor(s)PagesInfo
Front Matter
i-xx
Front Matter
1-1
Tensor Networks for Dimensionality Reduction, Big Data and Deep Learning
Andrzej Cichocki
3-49
Local Data Characteristics in Learning Classifiers from Imbalanced Data
Jerzy Błaszczyński; Jerzy Stefanowski
51-85
Dimensions of Semantic Similarity
Paweł Szmeja; Maria Ganzha; Marcin Paprzycki; Wiesław Pawłowski
87-125
Some Interesting Phenomenon Occurring During Self-learning Process with Its Psychological Interpretation
Ryszard Tadeusiewicz
127-139
Front Matter
141-141
On the Interpretation and Characterization of Echo State Networks Dynamics: A Complex Systems Perspective
Filippo Maria Bianchi; Lorenzo Livi; Cesare Alippi
143-167
Optimization of Ensemble Neural Networks with Type-1 and Interval Type-2 Fuzzy Integration for Forecasting the Taiwan Stock Exchange
Martha Pulido; Patricia Melin; Olivia Mendoza
169-181
Deep Neural Networks—A Brief History
Krzysztof J. Cios
183-200
Front Matter
201-201
Techniques for Construction and Integration of Rule Bases
Grzegorz J. Nalepa
203-223
New Aspects of Interpretability of Fuzzy Systems for Nonlinear Modeling
Krystian Łapa; Krzysztof Cpałka; Leszek Rutkowski
225-264
On the Intuitionistic Fuzzy Sets of n-th Type
Krassimir T. Atanassov; Peter Vassilev
265-274
Front Matter
275-275
MCTS/UCT in Solving Real-Life Problems
Jacek Mańdziuk
277-292
Interactive Cone Contraction for Evolutionary Mutliple Objective Optimization
Miłosz Kadziński; Michał K. Tomczyk; Roman Słowiński
293-309
A Review of Fuzzy and Mathematic Methods for Dynamic Parameter Adaptation in the Firefly Algorithm
Oscar Castillo; Carlos Soto; Fevrier Valdez
311-321
Front Matter
323-323
Computational Intelligence Methods in Personalized Pharmacotherapy
Adam E. Gawęda; Michael E. Brier
325-333
Chapters/HeadingsAuthor(s)PagesInfo
Showing 1 to 20 of 24 entries
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