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Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four fundamental methods of multivariate exploratory data analysis tha...Lees meer
This book includes relevant developments on observation-based, feature-based and model-based traditional and fuzzy clustering methods, feature-based a...Lees meer
Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four fundamental methods of multivariate exploratory data analysis tha...Lees meer
This valuable text addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks cov...Lees meer
This third edition covers today's most commonly used techniques in computational statistics while maintaining the same philosophy and writing style of...Lees meer
The second edition of this bestseller provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian ...Lees meer
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...Lees meer
Due to its data handling and modeling capabilities as well as its flexibility, R is becoming the most widely used software in bioinformatics. R Progra...Lees meer
Combinatorial Inference in Geometric Data Analysis gives an overview of multidimensional statistical inference methods applicable to clouds of points ...Lees meer
This valuable text addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks cov...Lees meer
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...Lees meer
Textual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R...Lees meer
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...Lees meer
Developed by Jean-Paul Benzérci more than 30 years ago, correspondence analysis as a framework for analyzing data quickly found widespread popularity ...Lees meer
This book is designed to provide a new framework for Data Science, based on a solid foundation in mathematics and computational science. It is written...Lees meer
This book provides a broad, accessible treatment of the theory and linguistic applications of semisupervised methods. It presents a brief history of t...Lees meer
Textual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R...Lees meer
This book includes relevant developments on observation-based, feature-based and model-based traditional and fuzzy clustering methods, feature-based a...Lees meer
The rapid advancement in the theoretical understanding of statistical and machine learning methods for semisupervised learning has made it difficult f...Lees meer
This book addresses the applications of extensively used regression models under a Bayesian framework. It emphasizes efficient Bayesian inference thro...Lees meer
This third edition covers today's most commonly used techniques in computational statistics while maintaining the same philosophy and writing style of...Lees meer
This book is designed to provide a new framework for Data Science, based on a solid foundation in mathematics and computational science. It is written...Lees meer
This book blends a modern statistical approach with extensive engineering applications and clearly delineates the steps for successfully modeling a pr...Lees meer
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...Lees meer