Bayesian networks for Ruby
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README.md

Bayesian Networks for Ruby ( bn4r )

bn4r is a bayesian networks library on ruby that provides the user with classes for create bayesian networks and diverse algorithms for solve them.

Its algorithms implementation are based on: S.Russell, P.Norving, "Artificial Intelligence, A Modern Approach", 2nd Edition.

Website: http://bn4r.rubyforge.org

Spanish Website: http://bn4r.rubyforge.org/es

Rubyforge Project: http://rubyforge.org/projects/bn4r

Dependencies

rgl-0.2.3 ( Ruby Graph Library ), http://rgl.rubyforge.org

Design principles

The library consists on the object BayesNet thinked to be filled with BayesNetNode, these objects are defined in bn.rb. BayesNet object is a especialization of RGL::DirectedAdjacencyGraph ( http://rgl.rubyforge.org ).

The file bn_algorithms.rb has the implementation of the inference algorithms that can be used to solve BayesNet structures.

Files bn_export.rb and bn_import.rb have methods for import and export bayesian networked in different formats.

Finally, a set of objects and methods are given to automaticly fill BayesNetNode probabilities tables.

Usage Examples

  1. Install the gem ( bn4r-0.9.0.gem )

    gem install bn4r

  2. Include the bn4r

    require 'bn4r'

  3. Create your first bayes net

     #Create BayesNet
     bn_aima = BayesNet.new
    
     # Create nodes for the Bayes Net (BayesNetNodes)
     burglary = BayesNetNode.new("Burglary")
     earthquake = BayesNetNode.new("Earthquake")
     alarm = BayesNetNode.new("Alarm")
     john_calls = BayesNetNode.new("JohnCalls")
     mary_calls = BayesNetNode.new("MaryCalls")
    
     # Add nodes ( vertex ) to the BayesNet
     bn_aima.add_vertex(burglary)
     bn_aima.add_vertex(earthquake)
     bn_aima.add_vertex(alarm)
     bn_aima.add_vertex(john_calls)
     bn_aima.add_vertex(mary_calls)
    
     # Add relations ( edges ) between nodes in the BayesNet
     bn_aima.add_edge(burglary,alarm)
     bn_aima.add_edge(earthquake,alarm)
     bn_aima.add_edge(alarm,john_calls)
     bn_aima.add_edge(alarm,mary_calls)
    
     # Assign probabilities to each node
     burglary.set_probability_table([], [0.001, 0.999] )
     earthquake.set_probability_table([], [0.002, 0.998] )
    
     alarm.set_probability_table([burglary,earthquake], [0.95, 0.05, 0.94, 0.06, 0.29, 0.71, 0.001,0.999] )
    
     john_calls.set_probability_table([alarm], [0.90,0.10,0.05,0.95])
     mary_calls.set_probability_table([alarm], [0.70,0.30,0.01,0.99])
    
  4. Solve it!

     # John and Mary are calling ...
     john_calls.set_value(true)  
     mary_calls.set_value(true)
    
     # Why?
     is_there_a_burglary = bn_aima.enumeration_ask( burglary, [john_calls, mary_calls] )
     puts "Call the police!" if is_there_a_burglary[0] > is_there_a_burglary[1]
    
     is_the_alarm_on = bn_aima.enumeration_ask( alarm, [john_calls, mary_calls] )
     puts "Run home, your alarm is distubing the neigborhood!" if is_the_alarm_on[0] > is_the_alarm_on[1]
    
     is_there_a_earthquake = bn_aima.enumeration_ask( earthquake, [john_calls, mary_calls] )
     puts "Calm yourself, there isn't a earthquake ;)" if is_there_a_earthquake[0] < is_there_a_earthquake[1]	
    
  5. See how your bayes net looks like

     #In .dot format
     bn_aima.to_dot
    
     # In Microsoft Belief Networks (.xbn) format
     # (download for free in: http://research.microsoft.com/adapt/MSBNx )
     bn_aima.to_xbn
    

Documentation

Documentation can be found at http://bn4r.rubyforge.org/rdoc or can be generated using rdoc tool under the source code with: rdoc README lib

Credits

Thanks to Núria Bel ( http://www.upf.edu/pdi/iula/nuria.bel ) for her work in this project without her it cannot be done.

Thanks to Ryan Dahl for his work in http://www.math.rochester.edu/people/grads/rld/bayesnets that was the inspiration of the project.

Also thanks to all the ruby community.

Copying/License

This work is developed by Sergio Espeja ( http://www.upf.edu/pdi/iula/sergio.espeja, sergio.espeja at gmail.com ) mainly in Institut Universitari de Lingüística Aplicada of Universitat Pompeu Fabra ( http://www.iula.upf.es ), and also in bee.com.es ( http://bee.com.es ).

It is free software, and may be redistributed under GPL license.

Support

Please contact me in http://rubyforge.org/projects/bn4r.