Pattern recognition

A comprehensive overview of high-performance pattern recognition techniques and approaches to Computational Molecular Biology This book surveys the developments of techniques and approaches on pattern recognition related to Computational Molecular Biology.

A comprehensive overview of high-performance pattern recognition techniques and approaches to Computational Molecular Biology This book surveys the developments of techniques and approaches on pattern recognition related to Computational Molecular Biology.

This book is the first of its kind to discuss error estimation with a model-based approach.

This book is the first of its kind to discuss error estimation with a model-based approach.

A unified, coherent treatment of current classifier ensemble methods, from fundamentals of pattern recognition to ensemble feature selection, now in its second edition The art and science of combining pattern classifiers has flourished into a prolific discipline since the first edition of Combining Pattern Classifiers was published in 2004.

A unified, coherent treatment of current classifier ensemble methods, from fundamentals of pattern recognition to ensemble feature selection, now in its second edition The art and science of combining pattern classifiers has flourished into a prolific discipline since the first edition of Combining Pattern Classifiers was published in 2004.

The first edition, published in 1973, has become a classic reference in the field.

Learn how to apply rough-fuzzy computing techniques to solve problems in bioinformatics and medical image processing Emphasizing applications in bioinformatics and medical image processing, this text offers a clear framework that enables readers to take advantage of the latest rough-fuzzy computing techniques to build working pattern recognition models.

Learn how to apply rough-fuzzy computing techniques to solve problems in bioinformatics and medical image processing Emphasizing applications in bioinformatics and medical image processing, this text offers a clear framework that enables readers to take advantage of the latest rough-fuzzy computing techniques to build working pattern recognition models.

An accessible undergraduate introduction to the concepts and methods in pattern recognition, machine learning and deep learning.

Now in its third edition, this book focuses on practical algorithms for mining data from even the largest datasets.

A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.

New to the second edition of this advanced text are several chapters on regression, including neural networks and deep learning.

An intuitive and accessible textbook covering both fundamentals and applications.

Covers mathematical and algorithmic foundations of data science: machine learning, high-dimensional geometry, and analysis of large networks.

Covers mathematical and algorithmic foundations of data science: machine learning, high-dimensional geometry, and analysis of large networks.

Provides a comprehensive textbook covering theory and practical examples for a course on data mining and data warehousing.

A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.

A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.

A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.

Distills key concepts from linear algebra, geometry, matrices, calculus, optimization, probability and statistics that are used in machine learning.

This undergraduate textbook introduces essential machine learning concepts in NLP in a unified and gentle mathematical framework.

This undergraduate textbook introduces essential machine learning concepts in NLP in a unified and gentle mathematical framework.

An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.

An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.

A comprehensive survey of the quickly developing discipline of cognitive linguistics, its rich methodology, key results, and interdisciplinary context.

A comprehensive survey of the quickly developing discipline of cognitive linguistics, its rich methodology, key results, and interdisciplinary context.

Take an exhilarating journey through the modern revolution in statistics with two of the ringleaders.

Take an exhilarating journey through the modern revolution in statistics with two of the ringleaders.

Sure to be influential, this book lays the foundations for the use of algebraic geometry in statistical learning theory.

Applications of combinatorics in bioformatics, text processing, combinatorial enumeration and fractal analysis.

This book provides a computational and algorithmic foundation for techniques in topological data analysis, with examples and exercises.

Shapes have been among man's fascinations from thestoneage to thespace age.

Computational Knowledge Vision: The First Footprints presents a novel, advanced framework which combines structuralized knowledge and visual models.

This book introduces different approaches to developing recommender systems that automate choice-making strategies to provide affordable, personal, and high-quality recommendations.

This book describes a range of string problems in computer science and molecular biology and the algorithms developed to solve them.

Describes the specifications and operation of barcodes for mobile devices, focussing on two-dimensional barcodes and recent developments.

Sure to be influential, this book lays the foundations for the use of algebraic geometry in statistical learning theory.

Covers core techniques of image capture and the display of monochrome and color images.

Suited for self-study, and will appeal to all working in computer graphics, machine vision and image processing.

Covers text mining and link detection algorithms, pre-processing techniques, knowledge representation, visualization and applications.

Biometrics are used in many situations of our daily lives, but we still don't fully understand the way they work and what potential lies behind them.

Self-contained and entertaining introduction to computational genomics, using a case-studies approach with Matlab demos.

Focuses on a few of the important clustering algorithms in the context of information retrieval.

A unique account of developing topic in data mining and machine learning.

This book provides a general framework for repeated game playing, adaptive data compression, sequential investments, sequential pattern analysis and other problems.

A review of the background material needed for correlation pattern recognition for graduate students and practitioners.

Presents recently developed algorithms for searching for simple, multiple and extended strings, regular expressions, exact and approximate matches.

The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation.

A timely convergence of two widely used disciplines Random Graphs for Statistical Pattern Recognition is the first book to address the topic of random graphs as it applies to statistical pattern recognition.