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2015, ISBN 9781107019652, xii, 249 pages
"What are the models used in phylogenetic analysis and what exactly is involved in Bayesian evolutionary analysis using Markov chain Monte Carlo (MCMC)... 
Bayesian statistical decision theory | bayesian analysis | Cladistic analysis | Informatique | Data processing | phylogenetics | Théorie de la décision bayésienne | Analyse cladistique
Book
Bioinformatics, ISSN 1367-4803, 04/2010, Volume 26, Issue 10, pp. 1372 - 1373
Motivation: Bayesian analysis through programs like BEAST (Drummond and Rumbaut, 2007) and MrBayes (Huelsenbeck et al., 2001) provides a powerful method for... 
EVOLUTIONARY | BIOTECHNOLOGY & APPLIED MICROBIOLOGY | BIOCHEMICAL RESEARCH METHODS | MATHEMATICAL & COMPUTATIONAL BIOLOGY | Computational Biology - methods | Models, Genetic | Software | Phylogeny | Bayes Theorem | Evolution, Molecular | Trees | Uncertainty | Webs | Tools | Mathematical models | Bayesian analysis | Bioinformatics | Computer programs
Journal Article
Systematic Biology, ISSN 1063-5157, 7/2014, Volume 63, Issue 4, pp. 534 - 542
Journal Article
BMC Evolutionary Biology, ISSN 1471-2148, 2013, Volume 13, Issue 1, pp. 221 - 221
Background: Bayesian phylogenetic analysis generates a set of trees which are often condensed into a single tree representing the whole set. Many methods exist... 
SPACE | EVOLUTIONARY BIOLOGY | PHYLOGENETIC TREES | ALGORITHM | GENETICS & HEREDITY | Models, Genetic | Phylogeny | Computer Simulation | Bayes Theorem | Bayesian statistical decision theory | Research | Analysis | Methods | Biological diversity | Trees | Age | Colleges & universities
Journal Article
08/2015, ISBN 9781107019652, 264
What are the models used in phylogenetic analysis and what exactly is involved in Bayesian evolutionary analysis using Markov chain Monte Carlo (MCMC) methods?... 
Bayesian statistical decision theory | Data processing | Cladistic analysis
eBook
Systematic Biology, ISSN 1063-5157, 03/2019, Volume 68, Issue 2, pp. 219 - 233
Abstract Bayesian inference methods rely on numerical algorithms for both model selection and parameter inference. In general, these algorithms require a high... 
EVOLUTIONARY BIOLOGY | PROPOSALS | parameter inference | SEQUENCES | MARGINAL LIKELIHOOD ESTIMATION | model selection | nested sampling | BAYESIAN-INFERENCE | Marginal likelihood
Journal Article
Journal of Machine Learning Research, ISSN 1532-4435, 09/2010, Volume 11, pp. 2533 - 2541
WEKA is a popular machine learning workbench with a development life of nearly two decades. This article provides an overview of the factors that we believe to... 
Machine learning software | Open source software | open source software | AUTOMATION & CONTROL SYSTEMS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | machine learning software
Journal Article
Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), ISSN 0302-9743, 2004, Volume 3056, pp. 3 - 12
Empirical research in learning algorithms for classification tasks generally requires the use of significance tests. The quality of a test is typically judged... 
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Conference Proceeding
Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), ISSN 0302-9743, 2004, Volume 3339, pp. 1089 - 1094
There are three main methods for handling continuous variables in naive Bayes classifiers, namely, the normal method (parametric approach), the kernel method... 
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Conference Proceeding
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN 0302-9743, 2006, Volume 4213, pp. 503 - 510
Multinomial naive Bayes (MNB) is a popular method for document classification due to its computational efficiency and relatively good predictive performance.... 
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Conference Proceeding
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN 0302-9743, 2009, Volume 5828, pp. 65 - 81
Conference Proceeding
Chemometrics and Intelligent Laboratory Systems, ISSN 0169-7439, 2011, Volume 109, Issue 2, pp. 139 - 145
In this article we demonstrate that, when evaluating a method for determining prediction intervals, interval size matters more than coverage because the latter... 
PLS regression | Experimental design | NIR | Prediction interval | REGRESSION | CHEMISTRY, ANALYTICAL | INSTRUMENTS & INSTRUMENTATION | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | STATISTICS & PROBABILITY | PARTIAL LEAST-SQUARES | AUTOMATION & CONTROL SYSTEMS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN 0302-9743, 2009, Volume 5828, pp. 38 - 50
Conference Proceeding
Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), ISSN 0302-9743, 2003, Volume 2903, Issue 2903, pp. 390 - 401
We show how a probabilistic interpretation of an ill defined problem, the problem of finding line breaks in a paragraph, can lead to an efficient new algorithm... 
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), ISSN 0302-9743, 2003, Volume 2903, Issue 2903, pp. 710 - 722
An important task in machine learning is determining which learning algorithm works best for a given data set. When the amount of data is small the same data... 
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN 0302-9743, 2006, Volume 4304, pp. 181 - 191
Conference Proceeding
International Journal of Approximate Reasoning, ISSN 0888-613X, 2007, Volume 45, Issue 2, pp. 386 - 401
In this article, we consider the computational aspects of deciding whether a conditional independence statement is implied by a list of conditional... 
Inference | Imset | Conditional independence | Algorithm | conditional independence | MARKOV PROPERTIES | inference | imset | MODELS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | algorithm | GRAPHS
Journal Article
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