CART

classification and regression tree (CART) C++ implementation

Table of Contents

• Introduction
• Data Format

Introduction

CART is a C++ implementation of classification and regression tree, which is a well-known algorithm for the DM (data mining). This is the soucecode of this implementation.

Data Format

The format of training and testing data file is:

: : ... . . .

Each line contains an instance and is ended by a '\n' character.

is an float value indicating the class id in classification, or the dependent variable value in regression. The range of class id should be from 1 to the size of classes. For example, the class id is 1, 2, 3 and 4 for a 4-class classification problem. The range of dependent variable value shold be within the real number set.

and : are sperated by a '\t' character. is a postive integer denoting the feature id. The range of feature id should be from 1 to the size of feature set. For example, the feature id is 1, 2, ... 9 or 10 if the dimension of feature set is 10. Indices must be in ASCENDING order. is a float denoting the feature value.

If the feature value equals 0, the : is encouraged to be neglected for the consideration of storage space and computational speed.

Labels in the testing file are only used to calculate accuracy or errors. If they are unknown, just fill the first column with any class labels.