mdlp/CHANGELOG.md

Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[2.1.1] - 2025-07-17

Internal Changes

• Updated Libtorch to version 2.7.1
• Updated ArffFiles library to version 1.2.1
• Enhance CMake configuration for better compatibility

[2.1.0] - 2025-06-28

Added

• Conan dependency manager support
• Technical analysis report

Changed

• Updated README.md
• Refactored library version and installation system
• Updated config variable names

Fixed

• Removed unneeded semicolon

[2.0.1] - 2024-07-22

Added

• CMake install target and make install command
• Flag to control sample building in Makefile

Changed

• Library name changed to fimdlp
• Updated version numbers across test files

Fixed

• Version number consistency in tests

[2.0.0] - 2024-07-04

Added

• Makefile with build & test actions for easier development
• PyTorch (libtorch) integration for tensor operations

Changed

• Major refactoring of build system
• Updated build workflows and CI configuration

Fixed

• BinDisc quantile calculation errors (#9)
• Error in percentile method calculation
• Integer type issues in calculations
• Multiple GitHub Actions configuration fixes

[1.2.1] - 2024-06-08

Added

• PyTorch tensor methods for discretization
• Improved library build system

Changed

• Refactored sample build process

Fixed

• Library creation and linking issues
• Multiple GitHub Actions workflow fixes

[1.2.0] - 2024-06-05

Added

• Discretizer - Abstract base class for all discretization algorithms (#8)
• BinDisc - K-bins discretization with quantile and uniform strategies (#7)
• Transform method to discretize values using existing cut points
• Support for multiple datasets in sample program
• Docker development container configuration

Changed

• Refactored system types throughout the library
• Improved sample program with better dataset handling
• Enhanced build system with debug options

Fixed

• Transform method initialization issues
• ARFF file attribute name extraction
• Sample program library binary separation

[1.1.3] - 2024-06-05

Added

• max_cutpoints hyperparameter for controlling algorithm complexity
• max_depth and min_length as configurable hyperparameters
• Enhanced sample program with hyperparameter support
• Additional datasets for testing

Changed

• Improved constructor design and parameter handling
• Enhanced test coverage and reporting
• Refactored build system configuration

Fixed

• Depth initialization in fit method
• Code quality improvements and smell fixes
• Exception handling in value cut point calculations

[1.1.2] - 2023-04-01

Added

• Comprehensive test suite with GitHub Actions CI
• SonarCloud integration for code quality analysis
• Enhanced build system with automated testing

Changed

• Improved GitHub Actions workflow configuration
• Updated project structure for better maintainability

Fixed

• Build system configuration issues
• Test execution and coverage reporting

[1.1.1] - 2023-02-22

Added

• Limits header for proper compilation
• Enhanced build system support

Changed

• Updated version numbering system
• Improved SonarCloud configuration

Fixed

• ValueCutPoint exception handling (removed unnecessary exception)
• Build system compatibility issues
• GitHub Actions token configuration

[1.1.0] - 2023-02-21

Added

• Classic algorithm implementation for performance comparison
• Enhanced ValueCutPoint logic with same_values detection
• Glass dataset support in sample program
• Debug configuration for development

Changed

• Refactored ValueCutPoint algorithm for better accuracy
• Improved candidate selection logic
• Enhanced sample program with multiple datasets

Fixed

• Sign error in valueCutPoint calculation
• Final cut value computation
• Duplicate dataset handling in sample

[1.0.0.0] - 2022-12-21

Added

• Initial release of MDLP (Minimum Description Length Principle) discretization library
• Core CPPFImdlp algorithm implementation based on Fayyad & Irani's paper
• Entropy and information gain calculation methods
• Sample program demonstrating library usage
• CMake build system
• Basic test suite
• ARFF file format support for datasets

Features

• Recursive discretization using entropy-based criteria
• Stable sorting with tie-breaking for identical values
• Configurable algorithm parameters
• Cross-platform C++ implementation

---

Release Notes

Version 2.x

• Breaking Changes: Library renamed to fimdlp
• Major Enhancement: PyTorch integration for improved performance
• New Features: Comprehensive discretization framework with multiple algorithms

Version 1.x

• Core Algorithm: MDLP discretization implementation
• Extensibility: Hyperparameter support and algorithm variants
• Quality: Comprehensive testing and CI/CD pipeline

Version 1.0.x

• Foundation: Initial stable implementation
• Algorithm: Core MDLP discretization functionality