Search Results for "bayesian"

UnBBayes is a probabilistic network framework written in Java. It has both a GUI and an API with inference, sampling, learning and evaluation. It supports Bayesian networks, influence diagrams, MSBN, OOBN, HBN, MEBN/PR-OWL, PRM, structure, parameter and incremental learning. Please, visit our wiki (https://sourceforge.net/p/unbbayes/wiki/Home/) for more information. Check out the license section (https://sourceforge.net/p/unbbayes/wiki/License/) for our licensing policy.

JAGS is Just Another Gibbs Sampler. It is a program for the statistical analysis of Bayesian hierarchical models by Markov Chain Monte Carlo.

...Citation: 1. Wang Q, Garrity GM, Tiedje JM, Cole JR. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol. 2007 Aug;73(16):5261-7. 2. Wang Q, Cole JR. Updated RDP taxonomy and RDP Classifier for more accurate taxonomic classification. Microbiol Resour Announc. 2024 Apr 11;13(4):e0106323.

Now in Github: https://github.com/dnaase/Bis-tools/tree/master/Bis-SNP BisSNP is a package based on the Genome Analysis Toolkit (GATK) map-reduce framework for genotyping in bisulfite treated massively parallel sequencing (Bisulfite-seq, NOMe-seq and RRBS) on Illumina platform. It uses bayesian inference with either manually specified or automatically estimated methylation probabilities of different cytosine context(not only CpG, CHH, CHG in Bisulfite-seq, but also GCH et.al. in other bisulfite treated sequencing) to determine genotypes and methylation levels simultaneously. It works for both of single-end and paired-end reads.Specificity and sensitivity has been validate by Illumina IM SNP array. ...

The Java Data Mining Package (JDMP) is a library that provides methods for analyzing data with the help of machine learning algorithms (e.g. clustering, classification, graphical models, neural networks, Bayesian networks, text processing, optimization).

Bayesian Network tools in Java (BNJ) is an open-source suite of software tools for research and development using graphical models of probability. It is published by the Kansas State University Laboratory for Knowledge Discovery in Databases (KDD).

The AdPreqFr4SL learning framework for Bayesian Network Classifiers is designed to handle the cost / performance trade-off and cope with concept drift. Our strategy for incorporating new data is based on bias management and gradual adaptation. Starting with the simple Naive Bayes, we scale up the complexity by gradually updating attributes and structure. Since updating the structure is a costly task, we use new data to primarily adapt the parameters and only if this is really necessary, do we adapt the structure. ...

This is a reference implementation of snoBAC, a Bayesian Classifier designed to predict box H/ACA snoRNAs in Caenorhabditis nematode genomes. For details of algorithm and data, see Wang and Ruvinsky (2009) RNA in press.

JBendge - Bayesian Estimation of Nonlinear Dynamic General Equilibrium Models. The project provides a toolkit together with a graphical user interface for the specification, solution, estimation and simulation of models.

Projeny (Probablistic Networks Generator in Java) is a graphical (Java SWT) front-end to BNT (Bayes Net Toolbox for Matlab). Projeny requires BNT, JMatLink and a Matlab back-end. There is no installable release package, but source code is available on SVN - please check out from SVN to use Projeny. Projeny was started with BNJ as the base.

The application Crimeblips provides up-to-date crime statistics for Berlin (Germany). It maps and visualizes crimes, allowing users to identify crime hot spots, trends and general patterns. Bayesian algorithms are used to extract relevant information.

Java/XML toolkit for research using Bayesian networks and other graphical models of probability (exact and approximate inference, structure learning, etc.)

RISO: distributed, heterogeneous Bayesian belief networks. Belief network: a probability model defined on an acyclic directed graph; distributed: nodes can be on different hosts; and heterogeneous: allowing different types of conditional distributions.

BaNU generates adaptable naive Bayesian networks from a database. The generated knowledge can be exported as Notation3 rules. Another feature is the ability to link with ILP systems such as Toplog and Aleph to find premises for the adaptable NBN's.

Data Mining Platform is a platform for data mining and analysis. It contains many of the new and sophisticated methods such as kernel-based classification, two-way clustering, bayesian networks, pattern recognition for time series analysis and many other