Search Results for "bayesian" - Page 6

...The model is described in full detail by Shephard and Sheppard in http://www.nuff.ox.ac.uk/users/shephard/papers/heavy.pdf. Access to functions for forecasting volatility, distribution analysis, and Bayesian estimation are also available. Many of the features have been tested and seem to work. Bugs and breakdowns are always inevitable and the package will continuously be updated in the future as improvements are made.

JProGraM (PRObabilistic GRAphical Models in Java) is a statistical machine learning library. It supports statistical modeling and data analysis along three main directions: (1) probabilistic graphical models (Bayesian networks, Markov random fields, dependency networks, hybrid random fields); (2) parametric, semiparametric, and nonparametric density estimation (Gaussian models, nonparanormal estimators, Parzen windows, Nadaraya-Watson estimator); (3) generative models for random networks (small-world, scale-free, exponential random graphs, Fiedler random fields), subgraph sampling algorithms (random walk, snowball, etc.), and spectral decomposition.

Provide a reference implementation of Moving Taylor Bayesian Regression, a method for nonparametric multi-dimensional function estimation with correlated errors from finite samples, as a Python package based on SciPy

A QGIS plugin to facilitate data processing for Bayesian spatial modeling. (doi: 10.1111/j.1600-0587.2010.06598.x) Alternative site: http://code.google.com/p/maps2winbugsplugin/

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. ...

GSP program are based on Bayesian framework with an EM algorithm to predict genome size iteratively, which is elegant in mathematics. The model first develop under the no sequencing error model, then extend to the sequencing errors containing model.

Given a set of seismic arrivals for one or more events, Bayesloc estimates the joint probability of event locations, corrections to travel time predictions, precision of arrival time measurements, and phase labels for the arrival times. Bayesloc also accepts probabilistic prior constraints on any of the input parameters, which can significantly tighten the distribution of all parameters.

...Webb, J. Boughton, F. Zheng, K.M. Ting and H. Salem (2012). Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive {Bayesian} classification. Machine Learning. 86(2):233-272.

...Webb, J. Boughton, F. Zheng, K.M. Ting and H. Salem (2012). Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive {Bayesian} classification. Machine Learning. 86(2):233-272.

Bis-SNP 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. ...

...You paint with the mouse into its dreams and it responds by changing what you painted gradually. There will also be an API for using it with other programs as a general high-dimensional space. Each pixel's brightness is its own dimension. Bayesian nodes have exactly 3 childs because that is all thats needed to do NAND in a fuzzy way as Bayes' Rule which is NAND at certain extremes. NAND can be used to create any logical system. In this early version, I'm still working on edge detection and its understanding of the same shapes at different brightnesses. This will be a module of the bigger Human AI Net project and will be used for adding realtime intuitive high dimensional intelligence in audio and visual interactions with the user.

The Automated Parameter Estimation and Model Selection Toolkit is a fast, parallelized MCMC engine written in C for Bayesian inference (parameter estimation and model selection).

A general purpose Bayesian Network Toolbox. This project seeks to take advantage of Python's best of both worlds style and create a package that is easy to use, easy to add on to, yet fast enough for real world use.

KolmoGNUS is a simple yet powerful program which recommends links to the user based on his tastes. Links are taken from selected del.icio.us feeds, and user tastes are learned with a bayesian inference technique.

Open Bayes is a python free/open library that allows users to easily create a bayesian network and perform inference/learning on it. It is mainly inspired from the Bayes Net Toolbox (BNT) but uses python as a base language. www.openbayes.org

Feedisto is your personal newspaper. Your newspaper is collocted from rss feeds, parsed by a bayesian filter to rate its relevance and served as a static html page or on a webserver to train the filter. Writing plugins is very easy.

jBNC is a Java toolkit for training, testing, and applying Bayesian Network Classifiers. Implemented classifiers have been shown to perform well in a variety of artificial intelligence, machine learning, and data mining applications.

This a wxWidets based GUI for BEST(Bayesian Estimation of Species Trees) found here http://www.stat.osu.edu/~dkp/BEST/introduction/.

Expediting cancer genetic and neurogenetic discovery through Bayesian Network Analysis of microarray data. Designed for genetics researchers, this takes in raw data (and a very small about of user input) and outputs reports usable by biologists.

Bayesian anti-spam classifier written in Python.

functs is a MATLAB class for Marginalize-Product-of-Functions (MPF) operations, which are commonly encountered in Bayesian inference, e.g., in sum product over probabilistic graphical models. functs abstracts multi-variate real functions over a grid.

Provides a set of tools for processing text, such as text extraction and classification. Classification implementations to be implemented include: Bayesian and Statistical (N-gram).

This project contains the source code and data for my paper "Transliterated Arabic Name Identification Using Machine Learning and Bayesian Inferencing". Code compiles and runs under MS .NET 4.0 -or- Mono 2.8.1.

BigFoot: Bayesian alignment and phylogenetic footprinting with MCMC. Annotates the locations of conserved elements in multiple sequence while correcting for alignment uncertainty and error.