Pattern Recognition And Classification
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Pattern Recognition And Classification
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Author : Geoff Dougherty
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-10-28
Pattern Recognition And Classification written by Geoff Dougherty and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-28 with Computers categories.
The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. However, despite the existence of a number of notable books in the field, the subject remains very challenging, especially for the beginner. Pattern Recognition and Classification presents a comprehensive introduction to the core concepts involved in automated pattern recognition. It is designed to be accessible to newcomers from varied backgrounds, but it will also be useful to researchers and professionals in image and signal processing and analysis, and in computer vision. Fundamental concepts of supervised and unsupervised classification are presented in an informal, rather than axiomatic, treatment so that the reader can quickly acquire the necessary background for applying the concepts to real problems. More advanced topics, such as semi-supervised classification, combining clustering algorithms and relevance feedback are addressed in the later chapters. This book is suitable for undergraduates and graduates studying pattern recognition and machine learning.
Pattern Classification
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Author : Richard O. Duda
language : en
Publisher: Wiley-Interscience
Release Date : 2001
Pattern Classification written by Richard O. Duda and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Business & Economics categories.
This edition has been completely revised, enlarged and formatted in two colours. It is a systematic account of the major topics in pattern recognition, based on the fundamental principles. It includes extensive examples.
Introduction To Pattern Recognition And Machine Learning
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Author : M Narasimha Murty
language : en
Publisher: World Scientific
Release Date : 2015-04-22
Introduction To Pattern Recognition And Machine Learning written by M Narasimha Murty and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-22 with Computers categories.
This book adopts a detailed and methodological algorithmic approach to explain the concepts of pattern recognition. While the text provides a systematic account of its major topics such as pattern representation and nearest neighbour based classifiers, current topics — neural networks, support vector machines and decision trees — attributed to the recent vast progress in this field are also dealt with. Introduction to Pattern Recognition and Machine Learning will equip readers, especially senior computer science undergraduates, with a deeper understanding of the subject matter.
Pattern Recognition Principles
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Author : Julius T. Tou
language : en
Publisher: Addison Wesley Publishing Company
Release Date : 1974
Pattern Recognition Principles written by Julius T. Tou and has been published by Addison Wesley Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 1974 with Computers categories.
The information-handling problem; Basic concepts of pattern recognition; Fundamental problems in pattern recognition system design; Design concepts and methodologies; Decision functions; Pattern classification by distance functions; Pattern classification by likelihood functions; Trainable pattern classifiers - the deterministic approach; Trainable pattern classifiers - the statistical approach; Pattern preprocessing and feature selection; Syntactic pattern recognition.
Pattern Classification Using Ensemble Methods
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Author : Lior Rokach
language : en
Publisher: World Scientific
Release Date : 2010
Pattern Classification Using Ensemble Methods written by Lior Rokach and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Computers categories.
1. Introduction to pattern classification. 1.1. Pattern classification. 1.2. Induction algorithms. 1.3. Rule induction. 1.4. Decision trees. 1.5. Bayesian methods. 1.6. Other induction methods -- 2. Introduction to ensemble learning. 2.1. Back to the roots. 2.2. The wisdom of crowds. 2.3. The bagging algorithm. 2.4. The boosting algorithm. 2.5. The AdaBoost algorithm. 2.6. No free lunch theorem and ensemble learning. 2.7. Bias-variance decomposition and ensemble learning. 2.8. Occam's razor and ensemble learning. 2.9. Classifier dependency. 2.10. Ensemble methods for advanced classification tasks -- 3. Ensemble classification. 3.1. Fusions methods. 3.2. Selecting classification. 3.3. Mixture of experts and meta learning -- 4. Ensemble diversity. 4.1. Overview. 4.2. Manipulating the inducer. 4.3. Manipulating the training samples. 4.4. Manipulating the target attribute representation. 4.5. Partitioning the search space. 4.6. Multi-inducers. 4.7. Measuring the diversity -- 5. Ensemble selection. 5.1. Ensemble selection. 5.2. Pre selection of the ensemble size. 5.3. Selection of the ensemble size while training. 5.4. Pruning - post selection of the ensemble size -- 6. Error correcting output codes. 6.1. Code-matrix decomposition of multiclass problems. 6.2. Type I - training an ensemble given a code-matrix. 6.3. Type II - adapting code-matrices to the multiclass problems -- 7. Evaluating ensembles of classifiers. 7.1. Generalization error. 7.2. Computational complexity. 7.3. Interpretability of the resulting ensemble. 7.4. Scalability to large datasets. 7.5. Robustness. 7.6. Stability. 7.7. Flexibility. 7.8. Usability. 7.9. Software availability. 7.10. Which ensemble method should be used?
Machine Learning And Data Mining In Pattern Recognition
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Author : Petra Perner
language : en
Publisher: Springer
Release Date : 2012-07-02
Machine Learning And Data Mining In Pattern Recognition written by Petra Perner and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-02 with Computers categories.
This book constitutes the refereed proceedings of the 8th International Conference, MLDM 2012, held in Berlin, Germany in July 2012. The 51 revised full papers presented were carefully reviewed and selected from 212 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and web mining.
Pattern Recognition
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Author : J.P. Marques de Sá
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Pattern Recognition written by J.P. Marques de Sá and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
Pattern recognition currently comprises a vast body of methods supporting the development of numerous applications in many different areas of activity. The generally recognized relevance of pattern recognition methods and techniques lies, for the most part, in the general trend of "intelligent" task emulation, which has definitely pervaded our daily life. Robot assisted manufacture, medical diagnostic systems, forecast of economic variables, exploration of Earth's resources, and analysis of satellite data are just a few examples of activity fields where this trend applies. The pervasiveness of pattern recognition has boosted the number of task specific methodologies and enriched the number of links with other disciplines. As counterbalance to this dispersive tendency there have been, more recently, new theoretical developments that are bridging together many of the classical pattern recognition methods and presenting a new perspective of their links and inner workings. This book has its origin in an introductory course on pattern recognition taught at the Electrical and Computer Engineering Department, Oporto University. From the initial core of this course, the book grew with the intent of presenting a comprehensive and articulated view of pattern recognition methods combined with the intent of clarifying practical issues with the aid of examples and applications to real-life data. The book is primarily addressed to undergraduate and graduate students attending pattern recognition courses of engineering and computer science curricula.
Decision Estimation And Classification
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Author : Charles W. Therrien
language : en
Publisher:
Release Date : 1989
Decision Estimation And Classification written by Charles W. Therrien and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with Pattern recognition systems categories.
Cognitively Diagnostic Assessment
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Author : Paul D. Nichols
language : en
Publisher: Psychology Press
Release Date : 1995
Cognitively Diagnostic Assessment written by Paul D. Nichols and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Education categories.
First Published in 1995. Routledge is an imprint of Taylor & Francis, an informa company.
Pattern Recognition And Classification In Time Series Data
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Author : Volna, Eva
language : en
Publisher: IGI Global
Release Date : 2016-07-22
Pattern Recognition And Classification In Time Series Data written by Volna, Eva and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-22 with Computers categories.
Patterns can be any number of items that occur repeatedly, whether in the behaviour of animals, humans, traffic, or even in the appearance of a design. As technologies continue to advance, recognizing, mimicking, and responding to all types of patterns becomes more precise. Pattern Recognition and Classification in Time Series Data focuses on intelligent methods and techniques for recognizing and storing dynamic patterns. Emphasizing topics related to artificial intelligence, pattern management, and algorithm development, in addition to practical examples and applications, this publication is an essential reference source for graduate students, researchers, and professionals in a variety of computer-related disciplines.