DecisionTree

The library is an implementation of the decision tree classification algorithm in C++. It is designed to be a robust tool for classification tasks within a supervised learning context.

Overview

Decision Tree (DT) is a powerful supervised learning method for classification and regression. They offer several compelling benefits, such as their simplicity of understanding and interpretation, and the minimal data preparation they require. The decisiontree library is crafted to provide clean and intuitive interfaces, ensuring ease of use and seamless integration into your projects.

Key Features

• Ease of Integration: Simple interfaces for hassle-free incorporation into existing projects.
• Simplicity: Straightforward logic that is easy to apply.
• Versatility: Effective for both classification problems.

System Requirements

• A C++ compiler that supports C++14 or later.
• CMake version 3.26.5 or higher.
• Google Test (GTest) version 1.14.0 or higher for running unit tests.

Installation Guide

To install the decisiontree library, follow these manual steps using CMake:

1. Clone or download and unzip the repository.
2. Navigate to the repository's root directory.
3. Execute the following commands:

cmake -S . -B build
cmake --build build
sudo make install  # Use 'sudo' if administrative privileges are required for installation.

This process will configure, build, and install the library on your system, making it ready for use in your C++ projects.

Example

We also provide three examples to demonstrate how to use the decisiontree library, see example1.cpp.

Ensure you have installed the decisiontree library and that it is available in your system's include path. Compile and run the example using the following command:

g++ -std=c++14 -I/path/to/decisiontree/include -o example1.out example1.cpp
./example1.out