Feature Extraction, Construction and Selection

Download Feature Extraction, Construction and Selection PDF Online Free

Author :
Publisher : Springer Science & Business Media
ISBN 13 : 1461557259
Total Pages : 418 pages
Book Rating : 4.58/5 ( download)

DOWNLOAD NOW!


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 Extraction

Download Feature Extraction PDF Online Free

Author :
Publisher : Springer
ISBN 13 : 3540354883
Total Pages : 765 pages
Book Rating : 4.88/5 ( download)

DOWNLOAD NOW!


Book Synopsis Feature Extraction by : Isabelle Guyon

Download or read book Feature Extraction written by Isabelle Guyon and published by Springer. This book was released on 2008-11-16 with total page 765 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is both a reference for engineers and scientists and a teaching resource, featuring tutorial chapters and research papers on feature extraction. Until now there has been insufficient consideration of feature selection algorithms, no unified presentation of leading methods, and no systematic comparisons.

Computational Methods of Feature Selection

Download Computational Methods of Feature Selection PDF Online Free

Author :
Publisher : CRC Press
ISBN 13 : 1584888792
Total Pages : 437 pages
Book Rating : 4.96/5 ( download)

DOWNLOAD NOW!


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 CRC Press. This book was released on 2007-10-29 with total page 437 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

Advances in Artificial Intelligence

Download Advances in Artificial Intelligence PDF Online Free

Author :
Publisher : Springer
ISBN 13 : 3540319522
Total Pages : 470 pages
Book Rating : 4.28/5 ( download)

DOWNLOAD NOW!


Book Synopsis Advances in Artificial Intelligence by : Balázs Kégl

Download or read book Advances in Artificial Intelligence written by Balázs Kégl and published by Springer. This book was released on 2005-05-03 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 18th conference of the Canadian Society for the Computational Study of Intelligence (CSCSI) continued the success of its predecessors. This set of - pers re?ects the diversity of the Canadian AI community and its international partners. AI 2005 attracted 135 high-quality submissions: 64 from Canada and 71 from around the world. Of these, eight were written in French. All submitted papers were thoroughly reviewed by at least three members of the Program Committee. A total of 30 contributions, accepted as long papers, and 19 as short papers are included in this volume. We invited three distinguished researchers to give talks about their current research interests: Eric Brill from Microsoft Research, Craig Boutilier from the University of Toronto, and Henry Krautz from the University of Washington. The organization of such a successful conference bene?ted from the coll- oration of many individuals. Foremost, we would like to express our apprec- tion to the Program Committee members and external referees, who provided timely and signi?cant reviews. To manage the submission and reviewing process we used the Paperdyne system, which was developed by Dirk Peters. We owe special thanks to Kellogg Booth and Tricia d’Entremont for handling the local arrangementsandregistration.WealsothankBruceSpencerandmembersofthe CSCSI executive for all their e?orts in making AI 2005 a successful conference.

Feature Extraction and Image Processing for Computer Vision

Download Feature Extraction and Image Processing for Computer Vision PDF Online Free

Author :
Publisher : Academic Press
ISBN 13 : 0123978246
Total Pages : 629 pages
Book Rating : 4.40/5 ( download)

DOWNLOAD NOW!


Book Synopsis Feature Extraction and Image Processing for Computer Vision by : Mark Nixon

Download or read book Feature Extraction and Image Processing for Computer Vision written by Mark Nixon and published by Academic Press. This book was released on 2012-12-18 with total page 629 pages. Available in PDF, EPUB and Kindle. Book excerpt: Feature Extraction and Image Processing for Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in Matlab. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated. As one reviewer noted, "The main strength of the proposed book is the exemplar code of the algorithms." Fully updated with the latest developments in feature extraction, including expanded tutorials and new techniques, this new edition contains extensive new material on Haar wavelets, Viola-Jones, bilateral filtering, SURF, PCA-SIFT, moving object detection and tracking, development of symmetry operators, LBP texture analysis, Adaboost, and a new appendix on color models. Coverage of distance measures, feature detectors, wavelets, level sets and texture tutorials has been extended. Named a 2012 Notable Computer Book for Computing Methodologies by Computing Reviews Essential reading for engineers and students working in this cutting-edge field Ideal module text and background reference for courses in image processing and computer vision The only currently available text to concentrate on feature extraction with working implementation and worked through derivation

Feature Engineering for Machine Learning

Download Feature Engineering for Machine Learning PDF Online Free

Author :
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491953195
Total Pages : 218 pages
Book Rating : 4.98/5 ( download)

DOWNLOAD NOW!


Book Synopsis Feature Engineering for Machine Learning by : Alice Zheng

Download or read book Feature Engineering for Machine Learning written by Alice Zheng and published by "O'Reilly Media, Inc.". This book was released on 2018-03-23 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. Each chapter guides you through a single data problem, such as how to represent text or image data. Together, these examples illustrate the main principles of feature engineering. Rather than simply teach these principles, authors Alice Zheng and Amanda Casari focus on practical application with exercises throughout the book. The closing chapter brings everything together by tackling a real-world, structured dataset with several feature-engineering techniques. Python packages including numpy, Pandas, Scikit-learn, and Matplotlib are used in code examples. You’ll examine: Feature engineering for numeric data: filtering, binning, scaling, log transforms, and power transforms Natural text techniques: bag-of-words, n-grams, and phrase detection Frequency-based filtering and feature scaling for eliminating uninformative features Encoding techniques of categorical variables, including feature hashing and bin-counting Model-based feature engineering with principal component analysis The concept of model stacking, using k-means as a featurization technique Image feature extraction with manual and deep-learning techniques

Feature Engineering and Selection

Download Feature Engineering and Selection PDF Online Free

Author :
Publisher : CRC Press
ISBN 13 : 1351609467
Total Pages : 266 pages
Book Rating : 4.63/5 ( download)

DOWNLOAD NOW!


Book Synopsis Feature Engineering and Selection by : Max Kuhn

Download or read book Feature Engineering and Selection written by Max Kuhn and published by CRC Press. This book was released on 2019-07-25 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of predictors for modeling and for nding the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.

Feature Selection for Data and Pattern Recognition

Download Feature Selection for Data and Pattern Recognition PDF Online Free

Author :
Publisher : Springer
ISBN 13 : 9783662508459
Total Pages : 0 pages
Book Rating : 4.51/5 ( download)

DOWNLOAD NOW!


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.

Lazy Learning

Download Lazy Learning PDF Online Free

Author :
Publisher : Springer Science & Business Media
ISBN 13 : 9401720533
Total Pages : 421 pages
Book Rating : 4.33/5 ( download)

DOWNLOAD NOW!


Book Synopsis Lazy Learning by : David W. Aha

Download or read book Lazy Learning written by David W. Aha and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited collection describes recent progress on lazy learning, a branch of machine learning concerning algorithms that defer the processing of their inputs, reply to information requests by combining stored data, and typically discard constructed replies. It is the first edited volume in AI on this topic, whose many synonyms include `instance-based', `memory-based'. `exemplar-based', and `local learning', and whose topic intersects case-based reasoning and edited k-nearest neighbor classifiers. It is intended for AI researchers and students interested in pursuing recent progress in this branch of machine learning, but, due to the breadth of its contributions, it should also interest researchers and practitioners of data mining, case-based reasoning, statistics, and pattern recognition.

Feature Extraction

Download Feature Extraction PDF Online Free

Author :
Publisher : Springer Science & Business Media
ISBN 13 : 3540354875
Total Pages : 765 pages
Book Rating : 4.71/5 ( download)

DOWNLOAD NOW!


Book Synopsis Feature Extraction by : Isabelle Guyon

Download or read book Feature Extraction written by Isabelle Guyon and published by Springer Science & Business Media. This book was released on 2006-07-20 with total page 765 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is both a reference for engineers and scientists and a teaching resource, featuring tutorial chapters and research papers on feature extraction. Until now there has been insufficient consideration of feature selection algorithms, no unified presentation of leading methods, and no systematic comparisons.