decisiontree
A Ruby library implementing the ID3 algorithm for decision tree learning with support for continuous and discrete datasets.
What is decisiontree?
Decision Tree is a Ruby library that implements the ID3 algorithm for building decision tree models from training data. It solves classification problems by learning rules from labeled datasets, allowing predictions on new data points. The library supports both continuous (numeric) and discrete (categorical) variables, making it adaptable to various data types.
Ruby developers and data practitioners who need a lightweight, native implementation of decision tree learning for prototyping, educational purposes, or integrating ML capabilities into Ruby applications.
Developers choose this library for its straightforward Ruby API, built-in visualization via Graphviz, and additional features like ensemble bagging and rule pruning that enhance model accuracy without external dependencies.
Overview
ID3-based implementation of the ML Decision Tree algorithm
Use Cases
Best For
- Learning decision tree algorithms in a Ruby environment
- Prototyping classification models with small to medium datasets
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