The toolkit for multivariate analysis, TMVA, provides a large set of advanced multivariate analysis techniques for signal/background classification. In addition, TMVA now also contains regression analysis, all embedded in a framework capable of handling the preprocessing of the data and the evaluation of the output, thus allowing a simple and convenient use of multivariate techniques. The analysis techniques implemented in TMVA can be invoked easily and the direct comparison of their performance allows the user to choose the most appropriate for a particular data analysis. This article gives an overview of the TMVA package and presents recently developed features
The aim of this tutorial is to present an overview of Multiple Factor Analysis (MFA, see Escofier an...
Revised and updated third edition offers a broader range of material Wide scope of methods and appli...
Fifth part of statistics course materials for the Sustainable Built Environment programme (master le...
TMVA-v3.8 Users Guide: 92 pages, 16 figures, numerous code examples version 4n high-energy physics, ...
Toolkit for Multivariate Analysis(TMVA) is a package in ROOT for machine learning algorithms for cla...
Multivariate classi cation methods based on machine learning techniques have become a fundamental in...
The workshop features overview talks about TMVA features and methods and a tutorial that covers clas...
This book offers a concise and well-organized introduction to multivariate statistical analysis meth...
ROOT is a framework for large-scale data analysis that provides basic and advanced statistical metho...
A practical guide for multivariate statistical techniques-- now updated and revised In recent years...
Describes the advances in computation and data storage that led to the introduction of many statisti...
The toolkit has been implemented as planned: The ground work for visualisation mappings and relation...
Real-world experiments are becoming increasingly more complex, needing techniques capable of trackin...
Focusing on high-dimensional applications, this 4th edition presents the tools and concepts used in ...
The aim of this tutorial is to present an overview of Multiple Factor Analysis (MFA, see Escofier an...
Revised and updated third edition offers a broader range of material Wide scope of methods and appli...
Fifth part of statistics course materials for the Sustainable Built Environment programme (master le...
TMVA-v3.8 Users Guide: 92 pages, 16 figures, numerous code examples version 4n high-energy physics, ...
Toolkit for Multivariate Analysis(TMVA) is a package in ROOT for machine learning algorithms for cla...
Multivariate classi cation methods based on machine learning techniques have become a fundamental in...
The workshop features overview talks about TMVA features and methods and a tutorial that covers clas...
This book offers a concise and well-organized introduction to multivariate statistical analysis meth...
ROOT is a framework for large-scale data analysis that provides basic and advanced statistical metho...
A practical guide for multivariate statistical techniques-- now updated and revised In recent years...
Describes the advances in computation and data storage that led to the introduction of many statisti...
The toolkit has been implemented as planned: The ground work for visualisation mappings and relation...
Real-world experiments are becoming increasingly more complex, needing techniques capable of trackin...
Focusing on high-dimensional applications, this 4th edition presents the tools and concepts used in ...
The aim of this tutorial is to present an overview of Multiple Factor Analysis (MFA, see Escofier an...
Revised and updated third edition offers a broader range of material Wide scope of methods and appli...
Fifth part of statistics course materials for the Sustainable Built Environment programme (master le...