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A Decision tree inducer (originally based on ID3).

It handles:

  • Numeric features
  • Categoric features
  • Asynchronous branch induction (for performance)


$ ./tr -h
Decision tree inducer
Version (of 2012-10-27): 0.1.1
All rights reserved Isak Karlsson 2012+

Example: tr -i <EXAMPLES> -y 0.66 -d 5 
     tr -i <EXAMPLES> -y 1 -d 0 

-y  [Percent training data] 
 A percentage of data that is used for
 training the model. The rest is used for validation.
 Default: 0.66
-d  [Maximum depth to paralellize]
 The depth in which the model is induced in paralell.
 Default: 5
-ag []
 Calculate gain in parallel even thought the MAX_DEPTH
 is reached (-d).
-o  []
 Output the tree model
-p  [N instances required to partition]
 Stop inducing a branch (and take the majority) when
 N is reached (for a given branch)
 Default: 10

For example,

$ git clone ....
$ cd erlang-id3/src
$ ./tr -i ../data/bank.txt -y 0.66 -d 10 -ag -p 100 -o > model.txt
 * File: "../data/bank.txt"
 * Split: 0.66
 * Depth: 10
 * Prune: 100
 * Gain async: true
Took: 1.159709 
Accuracy: 0.8792531390280398