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
Running:
* File: "../data/bank.txt"
* Split: 0.66
* Depth: 10
* Prune: 100
* Gain async: true
Took: 1.159709
Accuracy: 0.8792531390280398
BSD