Advances In Feature Selection For Data And Pattern Recognition

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Advances in Feature Selection for Data and Pattern Recognition

Author : Urszula Stańczyk
Publisher : Springer
ISBN 13 : 3319675885
Total Pages : 334 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Advances in Feature Selection for Data and Pattern Recognition by : Urszula Stańczyk

Download or read book Advances in Feature Selection for Data and Pattern Recognition written by Urszula Stańczyk and published by Springer. This book was released on 2017-11-16 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent developments and research trends in the field of feature selection for data and pattern recognition, highlighting a number of latest advances. The field of feature selection is evolving constantly, providing numerous new algorithms, new solutions, and new applications. Some of the advances presented focus on theoretical approaches, introducing novel propositions highlighting and discussing properties of objects, and analysing the intricacies of processes and bounds on computational complexity, while others are dedicated to the specific requirements of application domains or the particularities of tasks waiting to be solved or improved. Divided into four parts – nature and representation of data; ranking and exploration of features; image, shape, motion, and audio detection and recognition; decision support systems, it is of great interest to a large section of researchers including students, professors and practitioners.

Feature Selection for Data and Pattern Recognition

Author : Urszula Stańczyk
Publisher : Springer
ISBN 13 : 9783662456217
Total Pages : 355 pages
Book Rating : 4.4/5 (562 download)

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Book Synopsis Feature Selection for Data and Pattern Recognition by : Urszula Stańczyk

Download or read book Feature Selection for Data and Pattern Recognition written by Urszula Stańczyk and published by Springer. This book was released on 2015-01-10 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research book provides the reader with a selection of high-quality texts dedicated to current progress, new developments and research trends in feature selection for data and pattern recognition. Even though it has been the subject of interest for some time, feature selection remains one of actively pursued avenues of investigations due to its importance and bearing upon other problems and tasks. This volume points to a number of advances topically subdivided into four parts: estimation of importance of characteristic features, their relevance, dependencies, weighting and ranking; rough set approach to attribute reduction with focus on relative reducts; construction of rules and their evaluation; and data- and domain-oriented methodologies.

Feature Selection for Data and Pattern Recognition

Author : Urszula Stańczyk
Publisher : Springer
ISBN 13 : 9783662508459
Total Pages : 0 pages
Book Rating : 4.5/5 (84 download)

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Book Synopsis Feature Selection for Data and Pattern Recognition by : Urszula Stańczyk

Download or read book Feature Selection for Data and Pattern Recognition written by Urszula Stańczyk and published by Springer. This book was released on 2016-09-24 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research book provides the reader with a selection of high-quality texts dedicated to current progress, new developments and research trends in feature selection for data and pattern recognition. Even though it has been the subject of interest for some time, feature selection remains one of actively pursued avenues of investigations due to its importance and bearing upon other problems and tasks. This volume points to a number of advances topically subdivided into four parts: estimation of importance of characteristic features, their relevance, dependencies, weighting and ranking; rough set approach to attribute reduction with focus on relative reducts; construction of rules and their evaluation; and data- and domain-oriented methodologies.

Feature Extraction, Construction and Selection

Author : Huan Liu
Publisher : Springer Science & Business Media
ISBN 13 : 1461557259
Total Pages : 418 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Feature Extraction, Construction and Selection by : Huan Liu

Download or read book Feature Extraction, Construction and Selection written by Huan Liu and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is broad interest in feature extraction, construction, and selection among practitioners from statistics, pattern recognition, and data mining to machine learning. Data preprocessing is an essential step in the knowledge discovery process for real-world applications. This book compiles contributions from many leading and active researchers in this growing field and paints a picture of the state-of-art techniques that can boost the capabilities of many existing data mining tools. The objective of this collection is to increase the awareness of the data mining community about the research of feature extraction, construction and selection, which are currently conducted mainly in isolation. This book is part of our endeavor to produce a contemporary overview of modern solutions, to create synergy among these seemingly different branches, and to pave the way for developing meta-systems and novel approaches. Even with today's advanced computer technologies, discovering knowledge from data can still be fiendishly hard due to the characteristics of the computer generated data. Feature extraction, construction and selection are a set of techniques that transform and simplify data so as to make data mining tasks easier. Feature construction and selection can be viewed as two sides of the representation problem.

Feature Selection for Knowledge Discovery and Data Mining

Author : Huan Liu
Publisher : Springer Science & Business Media
ISBN 13 : 1461556899
Total Pages : 225 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Feature Selection for Knowledge Discovery and Data Mining by : Huan Liu

Download or read book Feature Selection for Knowledge Discovery and Data Mining written by Huan Liu and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: As computer power grows and data collection technologies advance, a plethora of data is generated in almost every field where computers are used. The com puter generated data should be analyzed by computers; without the aid of computing technologies, it is certain that huge amounts of data collected will not ever be examined, let alone be used to our advantages. Even with today's advanced computer technologies (e. g. , machine learning and data mining sys tems), discovering knowledge from data can still be fiendishly hard due to the characteristics of the computer generated data. Taking its simplest form, raw data are represented in feature-values. The size of a dataset can be measUJ·ed in two dimensions, number of features (N) and number of instances (P). Both Nand P can be enormously large. This enormity may cause serious problems to many data mining systems. Feature selection is one of the long existing methods that deal with these problems. Its objective is to select a minimal subset of features according to some reasonable criteria so that the original task can be achieved equally well, if not better. By choosing a minimal subset offeatures, irrelevant and redundant features are removed according to the criterion. When N is reduced, the data space shrinks and in a sense, the data set is now a better representative of the whole data population. If necessary, the reduction of N can also give rise to the reduction of P by eliminating duplicates.

Advances In Pattern Recognition And Artificial Intelligence

Author : Marleah Blom
Publisher : World Scientific
ISBN 13 : 9811239029
Total Pages : 277 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Advances In Pattern Recognition And Artificial Intelligence by : Marleah Blom

Download or read book Advances In Pattern Recognition And Artificial Intelligence written by Marleah Blom and published by World Scientific. This book was released on 2021-11-16 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes reviewed papers by international scholars from the 2020 International Conference on Pattern Recognition and Artificial Intelligence (held online). The papers have been expanded to provide more details specifically for the book. It is geared to promote ongoing interest and understanding about pattern recognition and artificial intelligence. Like the previous book in the series, this book covers a range of topics and illustrates potential areas where pattern recognition and artificial intelligence can be applied. It highlights, for example, how pattern recognition and artificial intelligence can be used to classify, predict, detect and help promote further discoveries related to credit scores, criminal news, national elections, license plates, gender, personality characteristics, health, and more.Chapters include works centred on medical and financial applications as well as topics related to handwriting analysis and text processing, internet security, image analysis, database creation, neural networks and deep learning. While the book is geared to promote interest from the general public, it may also be of interest to graduate students and researchers in the field.

Pattern Recognition and Data Mining

Author : Sameer Singh
Publisher : Springer
ISBN 13 : 3540287582
Total Pages : 713 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Pattern Recognition and Data Mining by : Sameer Singh

Download or read book Pattern Recognition and Data Mining written by Sameer Singh and published by Springer. This book was released on 2005-09-16 with total page 713 pages. Available in PDF, EPUB and Kindle. Book excerpt: This LNCS volume contains the papers presented at the 3rd International Conference on Advances in Pattern Recognition (ICAPR 2005) organized in August, 2005 in the beautiful city of Bath, UK.

Advances in Pattern Recognition

Author : José Francisco Martínez-Trinidad
Publisher : Springer
ISBN 13 : 3642159923
Total Pages : 395 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Advances in Pattern Recognition by : José Francisco Martínez-Trinidad

Download or read book Advances in Pattern Recognition written by José Francisco Martínez-Trinidad and published by Springer. This book was released on 2010-12-22 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation. This book constitutes the thoroughly refereed proceedings of the Second Mexican Conference on Pattern Recognition, MCPR 2010, held in Puebly, Mexico, in September 2010. The 39 revised papers were carefully reviewed and selected from 89 submissions and are organized in topical sections on computer vision and robotics, image processing, neural networks and signal processing, pattern recognition, data mining, natural language and document processing.

Advances in Pattern Recognition

Author : José Francisco Martinez-Trinidad
Publisher : Springer Science & Business Media
ISBN 13 : 3642159915
Total Pages : 395 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Advances in Pattern Recognition by : José Francisco Martinez-Trinidad

Download or read book Advances in Pattern Recognition written by José Francisco Martinez-Trinidad and published by Springer Science & Business Media. This book was released on 2010-09-13 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the Second Mexican Conference on Pattern Recognition, MCPR 2010, held in Puebly, Mexico, in September 2010. The 39 revised papers were carefully reviewed and selected from 89 submissions and are organized in topical sections on computer vision and robotics, image processing, neural networks and signal processing, pattern recognition, data mining, natural language and document processing.

Spectral Feature Selection for Data Mining (Open Access)

Author : Zheng Alan Zhao
Publisher : CRC Press
ISBN 13 : 1439862109
Total Pages : 224 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Spectral Feature Selection for Data Mining (Open Access) by : Zheng Alan Zhao

Download or read book Spectral Feature Selection for Data Mining (Open Access) written by Zheng Alan Zhao and published by CRC Press. This book was released on 2011-12-14 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spectral Feature Selection for Data Mining introduces a novel feature selection technique that establishes a general platform for studying existing feature selection algorithms and developing new algorithms for emerging problems in real-world applications. This technique represents a unified framework for supervised, unsupervised, and semisupervise

Advances in Pattern Recognition - ICAPR 2001

Author : Sameer Singh
Publisher : Springer
ISBN 13 : 3540447326
Total Pages : 491 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Advances in Pattern Recognition - ICAPR 2001 by : Sameer Singh

Download or read book Advances in Pattern Recognition - ICAPR 2001 written by Sameer Singh and published by Springer. This book was released on 2003-06-29 with total page 491 pages. Available in PDF, EPUB and Kindle. Book excerpt: The paper is organized as follows: In section 2, we describe the no- orientation-discontinuity interfering model based on a Gaussian stochastic model in analyzing the properties of the interfering strokes. In section 3, we describe the improved canny edge detector with an ed- orientation constraint to detect the edges and recover the weak ones of the foreground words and characters; In section 4, we illustrate, discuss and evaluate the experimental results of the proposed method, demonstrating that our algorithm significantly improves the segmentation quality; Section 5 concludes this paper. 2. The norm-orientation-discontinuity interfering stroke model Figure 2 shows three typical samples of original image segments from the original documents and their magnitude of the detected edges respectively. The magnitude of the gradient is converted into the gray level value. The darker the edge is, the larger is the gradient magnitude. It is obvious that the topmost strong edges correspond to foreground edges. It should be noted that, while usually, the foreground writing appears darker than the background image, as shown in sample image Figure 2(a), there are cases where the foreground and background have similar intensities as shown in Figure 2(b), or worst still, the background is more prominent than the foreground as in Figure 2(c). So using only the intensity value is not enough to differentiate the foreground from the background. (a) (b) (c) (d) (e) (f)

Advances in Security of Information and Communication Networks

Author : Ali Ismail Awad
Publisher : Springer
ISBN 13 : 3642405975
Total Pages : 260 pages
Book Rating : 4.6/5 (424 download)

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Book Synopsis Advances in Security of Information and Communication Networks by : Ali Ismail Awad

Download or read book Advances in Security of Information and Communication Networks written by Ali Ismail Awad and published by Springer. This book was released on 2013-08-15 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the International Conference on Advances in Security of Information and Communication Networks, Sec Net 2013, held in Cairo, Egypt, in September 2013. The 21 revised full papers presented were carefully reviewed and selected from 62 submissions. The papers are organized in topical sections on networking security; data and information security; authentication and privacy; security applications.

Pattern Recognition

Author : Wladyslaw Homenda
Publisher : John Wiley & Sons
ISBN 13 : 1119302838
Total Pages : 312 pages
Book Rating : 4.1/5 (193 download)

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Book Synopsis Pattern Recognition by : Wladyslaw Homenda

Download or read book Pattern Recognition written by Wladyslaw Homenda and published by John Wiley & Sons. This book was released on 2018-02-09 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new approach to the issue of data quality in pattern recognition Detailing foundational concepts before introducing more complex methodologies and algorithms, this book is a self-contained manual for advanced data analysis and data mining. Top-down organization presents detailed applications only after methodological issues have been mastered, and step-by-step instructions help ensure successful implementation of new processes. By positioning data quality as a factor to be dealt with rather than overcome, the framework provided serves as a valuable, versatile tool in the analysis arsenal. For decades, practical need has inspired intense theoretical and applied research into pattern recognition for numerous and diverse applications. Throughout, the limiting factor and perpetual problem has been data—its sheer diversity, abundance, and variable quality presents the central challenge to pattern recognition innovation. Pattern Recognition: A Quality of Data Perspective repositions that challenge from a hurdle to a given, and presents a new framework for comprehensive data analysis that is designed specifically to accommodate problem data. Designed as both a practical manual and a discussion about the most useful elements of pattern recognition innovation, this book: Details fundamental pattern recognition concepts, including feature space construction, classifiers, rejection, and evaluation Provides a systematic examination of the concepts, design methodology, and algorithms involved in pattern recognition Includes numerous experiments, detailed schemes, and more advanced problems that reinforce complex concepts Acts as a self-contained primer toward advanced solutions, with detailed background and step-by-step processes Introduces the concept of granules and provides a framework for granular computing Pattern recognition plays a pivotal role in data analysis and data mining, fields which are themselves being applied in an expanding sphere of utility. By facing the data quality issue head-on, this book provides students, practitioners, and researchers with a clear way forward amidst the ever-expanding data supply.

Computational Methods of Feature Selection

Author : Huan Liu
Publisher : Chapman and Hall/CRC
ISBN 13 : 9781584888789
Total Pages : 440 pages
Book Rating : 4.8/5 (887 download)

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Book Synopsis Computational Methods of Feature Selection by : Huan Liu

Download or read book Computational Methods of Feature Selection written by Huan Liu and published by Chapman and Hall/CRC. This book was released on 2007-10-29 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to increasing demands for dimensionality reduction, research on feature selection has deeply and widely expanded into many fields, including computational statistics, pattern recognition, machine learning, data mining, and knowledge discovery. Highlighting current research issues, Computational Methods of Feature Selection introduces the basic concepts and principles, state-of-the-art algorithms, and novel applications of this tool. The book begins by exploring unsupervised, randomized, and causal feature selection. It then reports on some recent results of empowering feature selection, including active feature selection, decision-border estimate, the use of ensembles with independent probes, and incremental feature selection. This is followed by discussions of weighting and local methods, such as the ReliefF family, k-means clustering, local feature relevance, and a new interpretation of Relief. The book subsequently covers text classification, a new feature selection score, and both constraint-guided and aggressive feature selection. The final section examines applications of feature selection in bioinformatics, including feature construction as well as redundancy-, ensemble-, and penalty-based feature selection. Through a clear, concise, and coherent presentation of topics, this volume systematically covers the key concepts, underlying principles, and inventive applications of feature selection, illustrating how this powerful tool can efficiently harness massive, high-dimensional data and turn it into valuable, reliable information.

Recent Advances in Ensembles for Feature Selection

Author : Verónica Bolón-Canedo
Publisher : Springer
ISBN 13 : 3319900803
Total Pages : 212 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Recent Advances in Ensembles for Feature Selection by : Verónica Bolón-Canedo

Download or read book Recent Advances in Ensembles for Feature Selection written by Verónica Bolón-Canedo and published by Springer. This book was released on 2018-04-30 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 that researchers 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.

Advances in Machine Learning and Data Science

Author : Damodar Reddy Edla
Publisher : Springer
ISBN 13 : 9811085692
Total Pages : 383 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Advances in Machine Learning and Data Science by : Damodar Reddy Edla

Download or read book Advances in Machine Learning and Data Science written by Damodar Reddy Edla and published by Springer. This book was released on 2018-05-16 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Volume of “Advances in Machine Learning and Data Science - Recent Achievements and Research Directives” constitutes the proceedings of First International Conference on Latest Advances in Machine Learning and Data Science (LAMDA 2017). The 37 regular papers presented in this volume were carefully reviewed and selected from 123 submissions. These days we find many computer programs that exhibit various useful learning methods and commercial applications. Goal of machine learning is to develop computer programs that can learn from experience. Machine learning involves knowledge from various disciplines like, statistics, information theory, artificial intelligence, computational complexity, cognitive science and biology. For problems like handwriting recognition, algorithms that are based on machine learning out perform all other approaches. Both machine learning and data science are interrelated. Data science is an umbrella term to be used for techniques that clean data and extract useful information from data. In field of data science, machine learning algorithms are used frequently to identify valuable knowledge from commercial databases containing records of different industries, financial transactions, medical records, etc. The main objective of this book is to provide an overview on latest advancements in the field of machine learning and data science, with solutions to problems in field of image, video, data and graph processing, pattern recognition, data structuring, data clustering, pattern mining, association rule based approaches, feature extraction techniques, neural networks, bio inspired learning and various machine learning algorithms.

Handbook of Pattern Recognition and Computer Vision

Author : C. H. Chen
Publisher : World Scientific
ISBN 13 : 9812384731
Total Pages : 1045 pages
Book Rating : 4.8/5 (123 download)

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Book Synopsis Handbook of Pattern Recognition and Computer Vision by : C. H. Chen

Download or read book Handbook of Pattern Recognition and Computer Vision written by C. H. Chen and published by World Scientific. This book was released on 1999 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference.