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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 (
* 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.