Verónica Bolón-Canedo – författare

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11 produkter

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11 produkter

Microarray Bioinformatics
AvVerónica Bolón-Canedo,Amparo Alonso-Betanzos
Inbunden, Engelska, 2019
2 460 kr
Skickas inom 10-15 vardagar
This book provides a comprehensive, interdisciplinary collection of the main, up-to-date methods, tools, and techniques for microarray data analysis, covering the necessary steps for the acquisition of the data, its preprocessing, and its posterior analysis. Featuring perspectives from biology, computer science, and statistics, the volume explores machine learning methods such as clustering, feature selection, classification, data normalization, and missing value imputation, as well as the statistical analysis of the data and the most popular computer tools to analyze microarray data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that will aid researchers in getting successful results. Cutting-edge and authoritative, Microarray Bioinformatics serves as an ideal guide for researchers and graduate students in bioinformatics, with basic knowledge in biology and computer science, and with a view to work with microarray datasets.
Microarray Bioinformatics
AvAmparo Alonso-Betanzos,Veronica Bolon-Canedo
E-bok
Engelska, 2019
2 224 kr
Läs direkt efter köp
This book provides a comprehensive, interdisciplinary collection of the main, up-to-date methods, tools, and techniques for microarray data analysis, covering the necessary steps for the acquisition of the data, its preprocessing, and its posterior analysis. Featuring perspectives from biology, computer science, and statistics, the volume explores machine learning methods such as clustering, feature selection, classification, data normalization, and missing value imputation, as well as the statistical analysis of the data and the most popular computer tools to analyze microarray data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that will aid researchers in getting successful results. Cutting-edge and authoritative, Microarray Bioinformatics serves as an ideal guide for researchers and graduate students in bioinformatics, with basic knowledge in biology and computer science, and with a view to work with microarray datasets.
Microarray Bioinformatics
AvVerónica Bolón-Canedo,Amparo Alonso-Betanzos
Häftad, Engelska, 2020
1 735 kr
Skickas inom 10-15 vardagar
This book provides a comprehensive, interdisciplinary collection of the main, up-to-date methods, tools, and techniques for microarray data analysis, covering the necessary steps for the acquisition of the data, its preprocessing, and its posterior analysis. Featuring perspectives from biology, computer science, and statistics, the volume explores machine learning methods such as clustering, feature selection, classification, data normalization, and missing value imputation, as well as the statistical analysis of the data and the most popular computer tools to analyze microarray data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that will aid researchers in getting successful results. Cutting-edge and authoritative, Microarray Bioinformatics serves as an ideal guide for researchers and graduate students in bioinformatics, with basic knowledge in biology and computer science, and with a view to work with microarray datasets.
Del 147 - Intelligent Systems Reference Library
Recent Advances in Ensembles for Feature Selection
AvVerónica Bolón-Canedo,Amparo Alonso-Betanzos
Häftad, Engelska, 2019
1 155 kr
Skickas inom 10-15 vardagar
This book offers a comprehensive overview of ensemble learning in the field of feature selection (FS), which consists of combining the output of multiple methods to obtain better results than any single method. It reviews various techniques for combining partial results, measuring diversity and evaluating ensemble performance. With the advent of Big Data, feature selection (FS) has become more necessary than ever to achieve dimensionality reduction. With so many methods available, it is difficult to choose the most appropriate one for a given setting, thus making the ensemble paradigm an interesting alternative.The authors first focus on the foundations of ensemble learning and classical approaches, before diving into the specific aspects of ensembles for FS, such as combining partial results, measuring diversity and evaluating ensemble performance. Lastly, the book shows examples of successful applications of ensembles for FS and introduces the new challenges thatresearchers now face. As such, the book offers a valuable guide for all practitioners, researchers and graduate students in the areas of machine learning and data mining.
Del 14640 - Lecture Notes in Computer Science
Advances in Artificial Intelligence
20th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2024, A Coruña, Spain, June 19–21, 2024, Proceedings
AvAmparo Alonso-Betanzos,Bertha Guijarro-Berdiñasm. fl.
Häftad, Engelska, 2024
753 kr
Skickas inom 10-15 vardagar
This book constitutes the refereed proceedings of the 20th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2024, held in A Coruña, Spain, during June 19–21, 2024.The 27 full papers presented in this book were carefully reviewed and selected from 38 submissions.CAEPIA is a forum open to researchers from all over the world to present and discuss their latest scientific and technological advances in Artificial Intelligence (AI).The papers cover such themes as: machine learning, search and optimization, creativity and AI, ontologies and knowledge graphs, education and AI, foundation, models and applications of AI, uncertainty in AI, ambient intelligence and smart environments, explainable and responsible AI, fuzzy logic, natural language processing, knowledge representation, reasoning and logic, constraints, search and planning, multi-agent systems, computer vision and robotics, and intelligent web and information retrieval.
Advances in Artificial Intelligence
20th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2024, A Coruña, Spain, June 19–21, 2024, Proceedings
AvAlicia Troncoso,Jose C. Riquelmem. fl.
E-bok
Engelska, 2024
852 kr
Läs direkt efter köp
This book constitutes the refereed proceedings of the 20th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2024, held in A Coruña, Spain, during June 19–21, 2024.
The 27 full papers presented in this book were carefully reviewed and selected from 38 submissions.
CAEPIA is a forum open to researchers from all over the world to present and discuss their latest scientific and technological advances in Artificial Intelligence (AI).
The papers cover such themes as: machine learning, search and optimization, creativity and AI, ontologies and knowledge graphs, education and AI, foundation, models and applications of AI, uncertainty in AI, ambient intelligence and smart environments, explainable and responsible AI, fuzzy logic, natural language processing, knowledge representation, reasoning and logic, constraints, search and planning, multi-agent systems, computer vision and robotics, and intelligent web and information retrieval.
Feature Selection for High-Dimensional Data
AvVerónica Bolón-Canedo,Noelia Sánchez-Maroñom. fl.
Inbunden, Engelska, 2015
581 kr
Skickas inom 10-15 vardagar
This book offers a coherent and comprehensive approach to feature subset selection in the scope of classification problems, explaining the foundations, real application problems and the challenges of feature selection for high-dimensional data.The authors first focus on the analysis and synthesis of feature selection algorithms, presenting a comprehensive review of basic concepts and experimental results of the most well-known algorithms. They then address different real scenarios with high-dimensional data, showing the use of feature selection algorithms in different contexts with different requirements and information: microarray data, intrusion detection, tear film lipid layer classification and cost-based features. The book then delves into the scenario of big dimension, paying attention to important problems under high-dimensional spaces, such as scalability, distributed processing and real-time processing, scenarios that open up new and interesting challenges for researchers.The book is useful for practitioners, researchers and graduate students in the areas of machine learning and data mining.
Feature Selection for High-Dimensional Data
AvAmparo Alonso-Betanzos,Noelia Sanchez-Maronom. fl.
E-bok
PDF, Engelska, 2015
732 kr
Läs direkt efter köp
This book offers a coherent and comprehensive approach to feature subset selection in the scope of classification problems, explaining the foundations, real application problems and the challenges of feature selection for high-dimensional data.
The authors first focus on the analysis and synthesis of feature selection algorithms, presenting a comprehensive review of basic concepts and experimental results of the most well-known algorithms.
They then address different real scenarios with high-dimensional data, showing the use of feature selection algorithms in different contexts with different requirements and information: microarray data, intrusion detection, tear film lipid layer classification and cost-based features. The book then delves into the scenario of big dimension, paying attention to important problems under high-dimensional spaces, such as scalability, distributed processing and real-time processing, scenarios that open up new and interesting challenges for researchers.
The book is useful for practitioners, researchers and graduate students in the areas of machine learning and data mining.
Feature Selection for High-Dimensional Data
AvVerónica Bolón-Canedo,Noelia Sánchez-Maroñom. fl.
Häftad, Engelska, 2016
579 kr
Skickas inom 10-15 vardagar
This book offers a coherent and comprehensive approach to feature subset selection in the scope of classification problems, explaining the foundations, real application problems and the challenges of feature selection for high-dimensional data.The authors first focus on the analysis and synthesis of feature selection algorithms, presenting a comprehensive review of basic concepts and experimental results of the most well-known algorithms. They then address different real scenarios with high-dimensional data, showing the use of feature selection algorithms in different contexts with different requirements and information: microarray data, intrusion detection, tear film lipid layer classification and cost-based features. The book then delves into the scenario of big dimension, paying attention to important problems under high-dimensional spaces, such as scalability, distributed processing and real-time processing, scenarios that open up new and interesting challenges for researchers.The book is useful for practitioners, researchers and graduate students in the areas of machine learning and data mining.
Del 147 - Intelligent Systems Reference Library
Recent Advances in Ensembles for Feature Selection
AvVerónica Bolón-Canedo,Amparo Alonso-Betanzos
Inbunden, Engelska, 2018
1 155 kr
Skickas inom 10-15 vardagar
This book offers a comprehensive overview of ensemble learning in the field of feature selection (FS), which consists of combining the output of multiple methods to obtain better results than any single method. It reviews various techniques for combining partial results, measuring diversity and evaluating ensemble performance. With the advent of Big Data, feature selection (FS) has become more necessary than ever to achieve dimensionality reduction. With so many methods available, it is difficult to choose the most appropriate one for a given setting, thus making the ensemble paradigm an interesting alternative.The authors first focus on the foundations of ensemble learning and classical approaches, before diving into the specific aspects of ensembles for FS, such as combining partial results, measuring diversity and evaluating ensemble performance. Lastly, the book shows examples of successful applications of ensembles for FS and introduces the new challenges thatresearchers now face. As such, the book offers a valuable guide for all practitioners, researchers and graduate students in the areas of machine learning and data mining.
Recent Advances in Ensembles for Feature Selection
AvAmparo Alonso-Betanzos,Veronica Bolon-Canedo
E-bok
Engelska, 2018
1 470 kr
Läs direkt efter köp
This book offers a comprehensive overview of ensemble learning in the field of feature selection (FS), which consists of combining the output of multiple methods to obtain better results than any single method. It reviews various techniques for combining partial results, measuring diversity and evaluating ensemble performance.
With the advent of Big Data, feature selection (FS) has become more necessary than ever to achieve dimensionality reduction. With so many methods available, it is difficult to choose the most appropriate one for a given setting, thus making the ensemble paradigm an interesting alternative.
The authors first focus on the foundations of ensemble learning and classical approaches, before diving into the specific aspects of ensembles for FS, such as combining partial results, measuring diversity and evaluating ensemble performance. Lastly, the book shows examples of successful applications of ensembles for FS and introduces the new challenges thatresearchers now face. As such, the book offers a valuable guide for all practitioners, researchers and graduate students in the areas of machine learning and data mining.

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Verónica Bolón-Canedo – författare

Microarray Bioinformatics

Microarray Bioinformatics

Microarray Bioinformatics

Recent Advances in Ensembles for Feature Selection

Advances in Artificial Intelligence

Advances in Artificial Intelligence

Feature Selection for High-Dimensional Data

Feature Selection for High-Dimensional Data

Feature Selection for High-Dimensional Data

Recent Advances in Ensembles for Feature Selection

Recent Advances in Ensembles for Feature Selection

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