R is an Open Source implementation of the S language. It works on multiple computing platforms and can be freely downloaded. ...
Lire la suite
"Kernel Based Algorithms for Mining Huge Data Sets" is the first book treating the fields of supervised, semi-supervised ...
Lire la suite
This book constitutes the thoroughly refereed joint postproceedings of the 5th International Workshop on Knowledge Discovery ...
Lire la suite
The4thInternationalWorkshoponKnowledgeDiscoveryinInductiveDatabases (KDID 2005) was held in Porto, Portugal, on October 3, ...
Lire la suite
Thebookisbasedonseveralyearsofexperienceofbothauthorsinteaching linear models at various levels. It gives an up-to-date account ...
Lire la suite
This book covers two major classes of mixed effects models—linear mixed models and generalized linear mixed models—and ...
Lire la suite
This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models, and ...
Lire la suite
Mathematics of Uncertainty" provides the basic ideas and foundations of uncertainty, covering the fields of mathematics ...
Lire la suite
This book teaches the art and statistical science of modern longitudinal data analysis. The author emphasizes specifying, ...
Lire la suite
Modeling Uncertainty: An Examination of Stochastic Theory, Methods, and Applications, is a volume undertaken by the friends ...
Lire la suite
This volume outlines a formal representation framework for modelling and reasoning with vague concepts in Artificial Intelligence. ...
Lire la suite
The importance of empirical economics and econometric methods has greatly in creased during the last 20 years due to the ...
Lire la suite
This book tries to strike a balance between mathematical foundations and statistical practice. The book provides a clear ...
Lire la suite
This book is a concise and readable introduction to Monte Carlo methods to find good approximate solutions to fuzzy optimization ...
Lire la suiteThis book brings together the latest genome base prediction models currently being used by statisticians, breeders and data ...
Lire la suite
Covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. ...
Lire la suite
This volume contains revised versions of selected papers presented during the biannual meeting of the Classification and ...
Lire la suite
This reference work and graduate level textbook considers a wide range of models and methods for analyzing and forecasting ...
Lire la suiteThe process of gathering and organizing news content has become a challenging task for emerging news sites, necessitating ...
Lire la suite
This second edition places increased emphasis on the use of alternative permutation statistical tests based on metric Euclidean ...
Lire la suite