Introduction To Pattern Recognition And Machine Learning
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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.
An Introduction To Pattern Recognition And Machine Learning
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Author : Paul Fieguth
language : en
Publisher: Springer Nature
Release Date : 2022-11-09
An Introduction To Pattern Recognition And Machine Learning written by Paul Fieguth and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-09 with Technology & Engineering categories.
The domains of Pattern Recognition and Machine Learning have experienced exceptional interest and growth, however the overwhelming number of methods and applications can make the fields seem bewildering. This text offers an accessible and conceptually rich introduction, a solid mathematical development emphasizing simplicity and intuition. Students beginning to explore pattern recognition do not need a suite of mathematically advanced methods or complicated computational libraries to understand and appreciate pattern recognition; rather the fundamental concepts and insights, eminently teachable at the undergraduate level, motivate this text. This book provides methods of analysis that the reader can realistically undertake on their own, supported by real-world examples, case-studies, and worked numerical / computational studies.
Introduction To Pattern Recognition And Machine Learning
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Author : M. Narasimha Murty
language : en
Publisher:
Release Date : 2015
Introduction To Pattern Recognition And Machine Learning written by M. Narasimha Murty and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with COMPUTERS categories.
Pattern Recognition And Machine Learning
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Author : Christopher M. Bishop
language : en
Publisher: Springer
Release Date : 2016-08-23
Pattern Recognition And Machine Learning written by Christopher M. Bishop and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-23 with Computers categories.
This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
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.
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.
Introduction To Pattern Recognition Statistical Structural Neural And Fuzzy Logic Approaches
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Author : Menahem Friedman
language : en
Publisher: World Scientific Publishing Company
Release Date : 1999-03-01
Introduction To Pattern Recognition Statistical Structural Neural And Fuzzy Logic Approaches written by Menahem Friedman and has been published by World Scientific Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-03-01 with Computers categories.
This book is an introduction to pattern recognition, meant for undergraduate and graduate students in computer science and related fields in science and technology. Most of the topics are accompanied by detailed algorithms and real world applications. In addition to statistical and structural approaches, novel topics such as fuzzy pattern recognition and pattern recognition via neural networks are also reviewed. Each topic is followed by several examples solved in detail. The only prerequisites for using this book are a one-semester course in discrete mathematics and a knowledge of the basic preliminaries of calculus, linear algebra and probability theory.
Pattern Recognition
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Author : Syed Thouheed Ahmed
language : en
Publisher: MileStone Research Publications
Release Date : 2021-08-01
Pattern Recognition written by Syed Thouheed Ahmed and has been published by MileStone Research Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-01 with Technology & Engineering categories.
This book covers the primary and supportive topics on pattern recognition with respect to beginners understand-ability. The aspects of pattern recognition is value added with an introductory of machine learning terminologies. This book covers the aspects of pattern validation, recognition, computation and processing. The initial aspects such as data representation and feature extraction is reported with supportive topics such as computational algorithms and decision trees. This text book covers the aspects as reported. Par t - I In this part, the initial foundation aspects of pattern recognition is discussed with reference to probabilities role in influencing a pattern occurrence, pattern extraction and properties. Introduction: Definition of Pattern Recognition, Applications, Datasets for Pattern Recognition, Different paradigms for Pattern Recognition, Introduction to probability, events, random variables, Joint distributions and densities, moments. Estimation minimum risk estimators, problems. Representation: Data structures for Pattern Recognition, Representation of clusters, proximity measures, size of patterns, Abstraction of Data set, Feature extraction, Feature selection, Evaluation. Par t - II In Part - II of the text, the mathematical representation and computation algorithms for extracting and evaluating patterns are discussed. The basic algorithms of machine learning classifiers with Nearest neighbor and Naive Bayes is reported with value added validation process using decision trees. Computational Algorithms: Nearest neighbor algorithm, variants of NN algorithms, use of NN for transaction databases, efficient algorithms, Data reduction, prototype selection, Bayes theorem, minimum error rate classifier, estimation of probabilities, estimation of probabilities, comparison with NNC, Naive Bayesclassifier, Bayesian belief network. Decision Trees: Introduction, Decision Tree for Pattern Recognition, Construction of Decision Tree, Splittingat the nodes, Over-fitting& Pruning, Examples.
Pattern Recognition And Machine Learning
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Author : Y. Anzai
language : en
Publisher: Morgan Kaufmann
Release Date : 1992-07-14
Pattern Recognition And Machine Learning written by Y. Anzai and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992-07-14 with Computers categories.
Recognition and learning by a computer. Representing information. Generation and transformation of representations. Pattern feature extraction. Pattern understanding methods. Learning concepts. Learning procedures. Learning based on logic. Learning by classification and discovery. Learning by neural networks.
Pattern Recognition
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Author : Brett Anderson
language : en
Publisher: Scientific e-Resources
Release Date : 2019-09-14
Pattern Recognition written by Brett Anderson and has been published by Scientific e-Resources this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-14 with categories.
Watching the environment and recognising patterns with the end goal of basic leadership is central to human instinct. This book manages the logical train that empowers comparable observation in machines through pattern recognition, which has application in differing innovation regions-character recognition, picture handling, modern computerization, web looks, discourse recognition, therapeutic diagnostics, target recognition, space science, remote detecting, information mining, biometric recognizable proof-to give some examples. This book is a composition of central subjects in pattern recognition utilizing an algorithmic approach. It gives a careful prologue to the ideas of pattern recognition and an efficient record of the real points in pattern recognition other than assessing the huge advance made in the field as of late. It incorporates fundamental strategies of pattern recognition, neural systems, bolster vector machines and choice trees. While hypothetical angles have been given due scope, the accentuation is more on the pragmatic. Pattern recognition has application in practically every field of human undertaking including topography, geology, space science and brain research. All the more particularly, it is helpful in bioinformatics, mental investigation, biometrics and a large group of different applications.