Advances in Feature Selection for Data and Pattern Recognition - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Advances in Feature Selection for Data and Pattern Recognition write by Urszula Stańczyk. This book was released on 2017-11-16. Advances in Feature Selection for Data and Pattern Recognition available in PDF, EPUB and Kindle. 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
Feature Selection for Data and Pattern Recognition - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Feature Selection for Data and Pattern Recognition write by Urszula Stańczyk. This book was released on 2015-01-10. Feature Selection for Data and Pattern Recognition available in PDF, EPUB and Kindle. 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
Feature Selection for Data and Pattern Recognition - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Feature Selection for Data and Pattern Recognition write by Urszula Stańczyk. This book was released on 2016-09-24. Feature Selection for Data and Pattern Recognition available in PDF, EPUB and Kindle. 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
Feature Extraction, Construction and Selection - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Feature Extraction, Construction and Selection write by Huan Liu. This book was released on 2012-12-06. Feature Extraction, Construction and Selection available in PDF, EPUB and Kindle. 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
Feature Selection for Knowledge Discovery and Data Mining - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Feature Selection for Knowledge Discovery and Data Mining write by Huan Liu. This book was released on 2012-12-06. Feature Selection for Knowledge Discovery and Data Mining available in PDF, EPUB and Kindle. 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.
