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Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four fundamental...Savoir plus
Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four fundamental...Savoir plus
The beginning of the age of artificial intelligence and machine learning has created new challenges and opportunities for data analysts, statisticians...Savoir plus
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Geometric Data Analysis designates the approach of Multivariate Statistics that conceptualizes the set of observations as a Euclidean cloud of points....Savoir plus
Written by a member of the R Development Core Team, this resource provides important information on how to work with research data. It contains a coll...Savoir plus
Focusing on the programming skills needed to use R for the solution of bioinformatics and computational biology problems, this practical guide covers ...Savoir plus
Geometric Data Analysis designates the approach of Multivariate Statistics that conceptualizes the set of observations as a Euclidean cloud of points....Savoir plus
Pattern Recognition Algorithms for Data Mining addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and exp...Savoir plus
To harness the high-throughput potential of DNA microarray technology, it is crucial that the analysis stages of the process are decoupled from the re...Savoir plus
Written by a member of the R Development Core Team, this resource provides important information on how to work with research data. It contains a coll...Savoir plus
Textual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R...Savoir plus
This book introduces the theory, methods, and applications of correspondence analysis. With an emphasis on data coding, it clearly demonstrates why th...Savoir plus
This book provides a comprehensive overview of music data analysis, from introductory material to advanced concepts. It covers various applications in...Savoir plus
This book provides a broad, accessible treatment of the theory and linguistic applications of semisupervised methods. It presents a brief history of t...Savoir plus
" Data Science Foundations is most welcome and, indeed, a piece of literature that the field is very much in need of...quite different from most data ...Savoir plus
This book provides a broad, accessible treatment of the theory and linguistic applications of semisupervised methods. It presents a brief history of t...Savoir plus
The beginning of the age of artificial intelligence and machine learning has created new challenges and opportunities for data analysts, statisticians...Savoir plus
Textual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R...Savoir plus
INLA stands for Integrated Nested Laplace Approximations, which is a new method for fitting a broad class of Bayesian regression models. No samples of...Savoir plus
This third edition covers today's most commonly used techniques in computational statistics while maintaining the same philosophy and writing style of...Savoir plus