Bayesian Network Resources

Raw Links

	- Whisky notes: http://www.whisky-pages.com/
		*** http://weka.wikispaces.com/Use+Weka+in+your+Java+code
		- http://cran.r-project.org/web/views/Bayesian.html - a metric shit tonne of packages for R
		- http://www.celiagreen.com/charlesmccreery/statistics/bayestutorial.pdf - Greate illustrated guide to bayesian trees
		- http://www.cs.waikato.ac.nz/~remco/weka_bn/bayesnet.html
		- http://en.wikipedia.org/wiki/Chain_rule_(probability) - Chain Rule of probablity
		- http://aima.cs.berkeley.edu/ - AI a Modern Approach (full HTML online)
		- http://www.labmedinfo.org/sites/default/files/file/publications/lmi339.pdf - Hierarchical Bayes Clasifiers for Uncertain Data
		- http://people.csail.mit.edu/jrennie/papers/icml03-nb.pdf - Naieve Bayes Text Classifiers
		- https://www.cra.com/pdf/bnetbuilderbackground.pdf - 
		- http://www.score-on-line.com/tmp/85.225.255.189.BWV772.PDF - Invention #1
		- UCI machine learning resources and datasets
		http://archive.ics.uci.edu/ml/
		- http://weka.wikispaces.com/Primer - weka command line primer


Gervill was designed to be generic synthesizer for Java. By adding gervill.jar to your classpath you should be able to load SoundFonts/DLS files using MidiSystem.getSoundBank(). And MidiSystem.getSynthesizer() should return instance of Gervill Synthesizer.


http://java.net/projects/gervill/pages/Home

Wave sound information
http://www.creative.com/soundblaster/soundfont/



Information
http://www.midi.org/

Links to the midi standard
http://www.midi.org/techspecs/index.php


General Statistics

http://en.wikipedia.org/wiki/Portal:Statistics


Cautioning against Causality:
http://www.jerrydallal.com/LHSP/cause.htm

Statistical Robustness
http://fisher.stat.wmich.edu/joe/Stat666/book/book.pdf

Statistical models for Causation

"Causal inferences can be drawn from non-experimental data. However, no mechanical rules can
be laid down for the activity. Since Hume, that is almost a truism. Instead, causal inference seems
to require an enormous investment of skill, intelligence, and hard work" (D.A. Friedman, "Statistical Models for Causation", p 19)

ftp://stat-www.berkeley.edu/pub/tech-reports/651.pdf


Uncertainty

There are some things that you know to be true, and others that you know to be false; yet, despite this extensive knowledge that you have, there remain many things whose truth or falsity is not known to you. We say that you are uncertain about them. You are uncertain, to varying degrees, about everything in the future; much of the past is hidden from you; and there is a lot of the present about which you do not have full information. Uncertainty is everywhere and you cannot escape from it.

“
”

Dennis Lindley, Understanding Uncertainty (2006)

Bayesian Stats and Reasoning

One of the best introductions to Bayesian Reasoning
http://yudkowsky.net/rational/bayes

Introduction to Bayesian Filtering
http://www.process.com/precisemail/bayesian_filtering.htm


Collection of Tutorials on Bayesian Networks and filtering
http://www.eecs.qmul.ac.uk/~norman/resources.html

Online Tutorial on Bayesian Belief Networks
http://www.eecs.qmul.ac.uk/~norman/BBNs/BBNs.htm

Comprehensive list of Bayes Network Packages
http://www.cs.ubc.ca/~murphyk/Bayes/bnsoft.html

Google's Directory of Bayes Networks Packages
http://directory.google.com/Top/Computers/Artificial_Intelligence/Belief_Networks/Software/

KDNet's list of software packages
http://www.kdnuggets.com/software/bayesian.html

Matt Heckman's Microsoft Research Page
http://research.microsoft.com/en-us/um/people/heckerman/

One of the the best survey's of the math of Bayesian networks
http://research.microsoft.com/en-us/um/people/heckerman/tutorial.pdf

Embedded Bayesian Network Classifiers
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.47.9933


Music, stats, and Bach

Statistics and Bach
http://www.google.com/search?sourceid=chrome&ie=UTF-8&q=John+Barnes+statistical+analysis+bach

Software Resources on Bayesian Reasoning

Weka Toolkit for ML
http://www.cs.waikato.ac.nz/ml/index.html

Older library on Bayesian Tools
http://bn4r.rubyforge.org/

http://www.igvita.com/2007/05/23/bayes-classification-in-ruby/