"FLSOM with Different Rates for Classification in Imbalanced Datasets"

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Book	Author(s)	Year	Publisher
Imbalanced Classification with Python: Better Metrics, Balance Skewed Classes, Cost-Sensitive Learning		2020	Machine Learning Mastery
Improved Classification Rates for Localized Algorithms under Margin Conditions	Ingrid Karin Blaschzyk	1st ed. 2020	Springer Fachmedien Wiesbaden
Papers Relating to Revised Rates of Assessment for Thirteen Different. . .	Bombay (India : State )	1866	Printed for Govt. at the Education Society's Press, Byculla
Statistical Methods for Imbalanced Data in Ecological and Biological Studies	Osamu Komori; Shinto Eguchi	1st ed. 2019	Springer Japan
Learning from Imbalanced Data Sets	Alberto Fernández; Salvador García; Mikel Galar; Ronaldo C. Prati; Bartosz Krawczyk; Francisco Herrera	1st ed. 2018	Springer International Publishing
Freight Rates: Official Classification Territory and Eastern Canada	Charles Curtice McCain	1913	La Salle extension university
Freight rates; : official classification territory and eastern Canada /	McCain, Charles Curtice,; Shelton, William Arthur,	[1913], [©1913]	La Salle extension university,
Algorithms and Data Structures for Massive Datasets	Dzejla Medjedovic, Emin Tahirovic	2021	Manning Publications
Algorithms and Data Structures for Massive Datasets	Dzejla Medjedovic, Emin Tahirovic	2022	Manning Publications
Algorithms and Data Structures for Massive Datasets	Dzejla Medjedovic, Emin Tahirovic	2022	Manning Publications Co.
Understanding Complex Datasets: Data Mining with Matrix Decompositions	David Skillicorn	2007	Routledge
Adjustable classification for libraries: with index.	James Duff Brown	1898	Library Supply
Imbalanced Learning: Foundations, Algorithms, and Applications	Haibo He; Yunqian Ma	2013	Wiley-IEEE Press
Mining of Massive Datasets	Jure Leskovec; Anand Rajaraman; Jeffrey David Ullman	2014-11	Cambridge University Press
Mining of massive datasets	Leskovec J., Rajaraman A., Ullman J.D	2014	Hachette Romans
Women and Political Inequality in Japan: Gender-Imbalanced Democracy	Mikiko Eto	2020	Routledge
Introducing. NET for Apache Spark: Distributed Processing for Massive Datasets	Ed Elliott	1st ed.	Apress
Classification: with index	Winchester repeating arms co. [from old catalog]	1914	The Ganser co.
The Classification of Religions: Different Methods, Their Advantages and. . .	Duren James Henderson Ward	1909	The Open courtpublishing company
Synthetic Datasets for Statistical Disclosure Control: Theory and Implementation	Jörg Drechsler	2011	Springer New York
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Chapter	Author(s)	Book	Book Authors	Year	Publisher
FLSOM with Different Rates for Classification in Imbalanced Datasets	Iván Machón-González; Hilario López-García	Artificial Neural Networks - ICANN 2008: 18th International Conference, Prague, Czech Republic, September 3-6, 2008, Proceedings Part I	Vera Kurkova-Pohlova; Jan Koutnik; Roman Neruda	2008	Springer Berlin Heidelberg
Working with Imbalanced Datasets		The Deep Learning with Keras Workshop: Learn how to define and train neural network models with just a few lines of code	Matthew Moocarme, Mahla Abdolahnejad, Ritesh Bhagwat	2020	Packt Publishing
Working with Imbalanced Datasets		The Deep Learning with Keras Workshop: An Interactive Approach to Understanding Deep Learning with Keras, 2nd Edition	Matthew Moocarme, Mahla Abdolahnejad, Ritesh Bhagwat	2020	Packt Publishing
Dialog Speech Sentiment Classification for Imbalanced Datasets	Sergis Nicolaou; Lambros Mavrides; Georgina Tryfou; Kyriakos Tolias; Konstantinos Panousis; Sotirios Chatzis et al.	Speech and Computer: 23rd International Conference, SPECOM 2021, St. Petersburg, Russia, September 27–30, 2021, Proceedings	Alexey Karpov; Rodmonga Potapova	1st ed. 2021	Springer International Publishing
Imbalanced Datasets		The Deep Learning with Keras Workshop: Learn how to define and train neural network models with just a few lines of code	Matthew Moocarme, Mahla Abdolahnejad, Ritesh Bhagwat	2020	Packt Publishing
Imbalanced Datasets		Applied Deep Learning with Keras: Solve complex real-life problems with the simplicity of Keras	Bhagwat, Ritesh; Abdolahnejad, Mahla; Moocarme, Matthew	2019	Packt Publishing Limited
Imbalanced Datasets		The Deep Learning with Keras Workshop: An Interactive Approach to Understanding Deep Learning with Keras, 2nd Edition	Matthew Moocarme, Mahla Abdolahnejad, Ritesh Bhagwat	2020	Packt Publishing
Imbalanced Datasets		Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection (Advances in Data Warehousing and Mining (Adwm) Book)	Yun Sing Koh, Nathan Rountree	2009	Information Science Reference
Strategies for Dealing with Imbalanced Datasets		The Data Science Workshop	Robert John; Samuel Asare; Andrew Worsley; Thomas Joseph; Anthony So	2020	Packt Publishing, Limited
Strategies for Dealing with Imbalanced Datasets		The Data Science Workshop: A New, Interactive Approach to Learning Data Science	Anthony So; Thomas V. Joseph; Robert Thas John; Andrew Worsley; Dr. Samuel Asare	2020	Packt Publishing
104 Dealing with imbalanced datasets		Real-World Natural Language Processing: Practical applications with deep learning	Masato Hagiwara	2021	Manning Publications
Handling Imbalanced Datasets		The Hundred-Page Machine Learning Book	Andriy Burkov	2019	Andriy Burkov
Handling Imbalanced Datasets		Machine Learning Engineering	Andriy Burkov	2020
Cross-Validation for Imbalanced Datasets		Imbalanced Classification with Python: Better Metrics, Balance Skewed Classes, Cost-Sensitive Learning		2020	Machine Learning Mastery
Classification Accuracy Comparison for Imbalanced Datasets with Its Balanced Counterparts Obtained by Different Sampling Techniques	Tilottama Goswami; Uponika Barman Roy	ICCCE 2020: Proceedings of the 3rd International Conference on Communications and Cyber Physical Engineering	Amit Kumar; Stefan Mozar	1st ed. 2021	Springer Nature Singapore
Applying Resampling Methods for Imbalanced Datasets to Not So Imbalanced Datasets	Olatz Arbelaitz; Ibai Gurrutxaga; Javier Muguerza; Jesús María Pérez	Advances in Artificial Intelligence: 15th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2013, Madrid, September 17-20, 2013, Proceedings	Concha Bielza; Antonio Salmerón; Amparo Alonso-Betanzos; J. Ignacio Hidalgo; Luis Martínez; Alicia Troncoso; Emilio Corchado; Juan M. Corchado	2013	Springer Berlin Heidelberg
Classification with Imbalanced Data		Matlab. Statistics and Machine Learning Toolbox. User's Guide		2021	MathWorks
Classification with Imbalanced Data		MATLAB Statistics and Machine Learning Toolbox™ User's Guide	The MathWorks, Inc.	2020	The MathWorks, Inc.
ARCID: A New Approach to Deal with Imbalanced Datasets Classification	Safa Abdellatif; Mohamed Ali Ben Hassine; Sadok Ben Yahia; Amel Bouzeghoub	SOFSEM 2018: Theory and Practice of Computer Science: 44th International Conference on Current Trends in Theory and Practice of Computer Science, Krems, Austria, January 29 - February 2, 2018, Proceedings	A Min Tjoa; Ladjel Bellatreche; Stefan Biffl; Jan van Leeuwen; Jiří Wiedermann	1st ed. 2018	Springer International Publishing
Imbalanced Classification		Modern Mainframe Development: COBOL, Databases, and Next-Generation Approaches	Tom Taulli	2022	O'Reilly Media
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