BayesNet/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.

[Unreleased]

Added

• Library logo generated with https://openart.ai to README.md
• Link to the coverage report in the README.md coverage label.
• convergence_best hyperparameter to the BoostAODE class, to control the way the prior accuracy is computed if convergence is set. Default value is false.
• SPnDE model.
• A2DE model.
• A2DE & SPnDE tests.
• Add tests to reach 99% of coverage.

Internal

• Create library ShuffleArffFile to limit the number of samples with a parameter and shuffle them.
• Refactor catch2 library location to test/lib
• Refactor loadDataset function in tests.
• Remove conditionalEdgeWeights method in BayesMetrics.
• Refactor Coverage Report generation.

[1.0.5] 2024-04-20

Added

• Install command and instructions in README.md
• Prefix to install command to install the package in the any location.
• The 'block_update' hyperparameter to the BoostAODE class, to control the way weights/significances are updated. Default value is false.
• Html report of coverage in the coverage folder. It is created with make viewcoverage
• Badges of coverage and code quality (codacy) in README.md. Coverage badge is updated with make viewcoverage
• Tests to reach 97% of coverage.
• Copyright header to source files.
• Diagrams to README.md: UML class diagram & dependency diagram
• Action to create diagrams to Makefile: make diagrams

Changed

• Sample app now is a separate target in the Makefile and shows how to use the library with a sample dataset
• The worse model count in BoostAODE is reset to 0 every time a new model produces better accuracy, so the tolerance of the model is meant to be the number of consecutive models that produce worse accuracy.
• Default hyperparameter values in BoostAODE: bisection is true, maxTolerance is 3, convergence is true

Removed

• The 'predict_single' hyperparameter from the BoostAODE class.
• The 'repeatSparent' hyperparameter from the BoostAODE class.

[1.0.4] 2024-03-06

Added

• Change ascending hyperparameter to order with these possible values {"asc", "desc", "rand"}, Default is "desc".
• Add the predict_single hyperparameter to control if only the last model created is used to predict in boost training or the whole ensemble (all the models built so far). Default is true.
• sample app to show how to use the library (make sample)

Changed

• Change the library structure adding folders for each group of classes (classifiers, ensembles, etc).
• The significances of the models generated under the feature selection algorithm are now computed after all the models have been generated and an α_t value is computed and assigned to each model.

[1.0.3] 2024-02-25

Added

• Voting / probability aggregation in Ensemble classes
• predict_proba method in Classifier
• predict_proba method in BoostAODE
• predict_voting parameter in BoostAODE constructor to use voting or probability to predict (default is voting)
• hyperparameter predict_voting to AODE, AODELd and BoostAODE (Ensemble child classes)
• tests to check predict & predict_proba coherence

[1.0.2] - 2024-02-20

Fixed

• Fix bug in BoostAODE: do not include the model if epsilon sub t is greater than 0.5
• Fix bug in BoostAODE: compare accuracy with previous accuracy instead of the first of the ensemble if convergence true

[1.0.1] - 2024-02-12

Added

• Notes in Classifier class
• BoostAODE: Add note with used features in initialization with feature selection
• BoostAODE: Add note with the number of models
• BoostAODE: Add note with the number of features used to create models if not all features are used
• Test version number in TestBayesModels
• Add tests with feature_select and notes on BoostAODE

Fixed

• Network predict test
• Network predict_proba test
• Network score test