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QUEST is proposed by Loh and Shih (1997), and stands for Quick, Unbiased, Efficient, Statistical Tree. It is a tree-structured classification algorithm that yields a binary decision tree. A comparison study of QUEST and other algorithms was conducted by Lim et al (2000).

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QuestDecisionTree

Quest decision tree is an open source software project for training decision classification tree with Quest algorithm proposed by Loh and Shih (1997) and stands for Quick, Unbiased, Efficient, Statistical Tree. It is a tree-structured classification algorithm that yields a binary decision tree. A comparison study of QUEST and other algorithms was conducted by Lim et al (2000). The project was implemented with c++ language ,trained and tested successfully.

Dependencies

Before you run the program, you need some libraries intalled in your machine.

g++, gsl, cmake

Installation

cd /../QuestDecisionTree

mkdir build

cd build

cmake ../

make

./QuestDecisionTree trainingdata.csv matadata.txt testdata.csv

(make sure the file trainingdata.csv matadata.txt testdata.csv exists in your executable directory)

Reference

Wei-Yin Loh and Yu-Shan Shih.Split selection methods for classification tree.

About

QUEST is proposed by Loh and Shih (1997), and stands for Quick, Unbiased, Efficient, Statistical Tree. It is a tree-structured classification algorithm that yields a binary decision tree. A comparison study of QUEST and other algorithms was conducted by Lim et al (2000).

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