igrigorik / decisiontree

ID3-based implementation of the ML Decision Tree algorithm

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decisiontree / CHANGELOG.txt
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0.1.0 - Apr. 04/07
  * ID3 algorithms for continuous and discrete cases
  * Graphviz component to visualize the learned tree
 
0.2.0 - Jul. 07/07
  * Modified and improved by Jose Ignacio (joseignacio.fernandez@gmail.com)
  * Added support for multiple, and symbolic outputs and graphing of continuos trees.
  * Modified to return the default value when no branches are suitable for the input.
  * Refactored entropy code.
 
0.3.0 - Sept. 15/07
  * ID3Tree can now handle inconsistent datasets.
  * Ruleset is a new class that trains an ID3Tree with 2/3 of the training data,
    converts it into a set of rules and prunes the rules with the remaining 1/3
    of the training data (in a C4.5 way).
  * Bagging is a bagging-based trainer (quite obvious), which trains 10 Ruleset
    trainers and when predicting chooses the best output based on voting.