BibSonomy bookmarks for /concept/tag/Bayes

Probability Theory As Extended Logic

edna_foobar — 2008-07-29T22:29:28+02:00

ci-bayes: Home

fmeyer — 2008-06-21T17:18:35+02:00

This project contains Naive and Fishers bayesian classifiers, as described in Toby Segaran's book "Programming Collective Intelligence." The book has pytho...This project contains Naive and Fishers bayesian classifiers, as described in Toby Segaran's book "Programming Collective Intelligence." The book has python implementations; this is a Java implementation.

icml2008@helsinki.fi

fsteeg — 2008-03-23T20:39:55+01:00

Decision Tree Learning in Ruby - igvita.com

fmeyer — 2008-03-02T02:34:14+01:00

You've built a vibrant community of Family Guy enthusiasts. The SVD recommendation algorithm took your site to the next level by allowing you to leverage t...You've built a vibrant community of Family Guy enthusiasts. The SVD recommendation algorithm took your site to the next level by allowing you to leverage the implicit knowledge of your community. But now you're ready for the next iteration - you are about

BBR: Bayesian Logistic Regression

beate — 2008-01-30T15:07:28+01:00

jBNC - Bayesian Network Classifier Toolbox

fsteeg — 2007-12-18T02:26:48+01:00

mozdev.org - bayesjunktool: index

creckord — 2007-11-14T16:29:51+01:00

David MacKay: Information Theory, Inference, and Learning Algorithms: The Book

pantounina — 2007-09-04T16:55:38+02:00

Free good book on Probabilty

HBC: Hierarchical Bayes Compiler

fsteeg — 2007-08-30T18:36:38+02:00

HBC is a toolkit for implementing hierarchical Bayesian models.

Classifier4J - Classifier4J

cschenk — 2007-08-14T16:36:47+02:00

Classifier4J is a Java library designed to do text classification.

[0708.0171] Virtual screening with support vector machines and structure kernels

a_olympia — 2007-08-05T12:13:09+02:00

Belief Propagation Visualized

fsteeg — 2007-07-31T18:09:06+02:00

In order to better understand complex Belief-Propagation models tested with our simulator we have identified a strong need for a simple visualization tool ...In order to better understand complex Belief-Propagation models tested with our simulator we have identified a strong need for a simple visualization tool that will grant us insight of the tested graphs.

Bayesian probability - Wikipedia, the free encyclopedia

fmeyer — 2007-06-05T08:19:46+02:00

Bayesian probability is an interpretation of probability suggested by Bayesian theory, which holds that the concept of probability can be defined as the de...Bayesian probability is an interpretation of probability suggested by Bayesian theory, which holds that the concept of probability can be defined as the degree to which a person believes a proposition. Bayesian theory also suggests that Bayes' theorem can

MERL – TR2001-022 – Understanding Belief Propagation and its Generalizations

fsteeg — 2007-05-31T17:33:25+02:00

"We explain the principles behind the belief propagation (BP) algorithm, which is an efficient way to solve inference problems based on passing local messa..."We explain the principles behind the belief propagation (BP) algorithm, which is an efficient way to solve inference problems based on passing local messages."

Homepage of Judea Pearl

fsteeg — 2007-05-31T16:15:49+02:00

Judea Pearl is one of the pioneers of Bayesian networks and the probabilistic approach to artificial intelligence. Invented the belief propagation algorith...Judea Pearl is one of the pioneers of Bayesian networks and the probabilistic approach to artificial intelligence. Invented the belief propagation algorithm.

Probabilistic Networks — An Introduction to

fsteeg — 2007-05-24T19:07:46+02:00

An Intuitive Explanation of Bayesian Reasoning

fsteeg — 2007-05-01T23:59:56+02:00

"Maybe you're a girl looking for a boyfriend, but the boy you're interested in refuses to date anyone who "isn't Bayesian". What matters is that Bayes is ..."Maybe you're a girl looking for a boyfriend, but the boy you're interested in refuses to date anyone who "isn't Bayesian". What matters is that Bayes is cool, and if you don't know Bayes, you aren't cool."

Lexical Disambiguation in Machine Translation with Latent Semantic Analysis

fsteeg — 2007-03-11T09:16:45+01:00

As the use of a Bayesian probability calculation on a simple co-occurrence frequency table created from the same data has similar disambiguation capabiliti...As the use of a Bayesian probability calculation on a simple co-occurrence frequency table created from the same data has similar disambiguation capabilities, the paper also incorporates comparison of LSA with the Bayesian model.

Word Sense Disambiguation based on improved Bayesian classifiers

fsteeg — 2007-03-11T06:27:00+01:00

In this paper, we perform WSD study based on large scale real-world corpus using two unsupervised learning algorithms based on ±n-improved Bayesian model a...In this paper, we perform WSD study based on large scale real-world corpus using two unsupervised learning algorithms based on ±n-improved Bayesian model and Dependency Grammar (DG)-improved Bayesian model.

Naive Bayes and Exemplar-Based approaches to Word Sense Disambiguation Revisited - Escudero, Marquez, Rigau (ResearchIndex)

fsteeg — 2007-03-11T06:24:14+01:00

This paper describes an experimental comparison between two standard supervised learning methods, namely Naive Bayes and Exemplar--based classification, on...This paper describes an experimental comparison between two standard supervised learning methods, namely Naive Bayes and Exemplar--based classification, on the Word Sense Disambiguation (WSD) problem.