95 lines
3.9 KiB
Markdown
95 lines
3.9 KiB
Markdown
# Changelog
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All notable changes to this project will be documented in this file.
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
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and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## [Unreleased]
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### Added
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- Add the Library logo generated with <https://openart.ai> to README.md
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- Add link to the coverage report in the README.md coverage label.
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- Add the *convergence_best* hyperparameter to the BoostAODE class, to control the way the prior accuracy is computed if convergence is set. Default value is *false*.
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### Internal
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- Refactor library ArffFile to limit the number of samples with a parameter.
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- Refactor tests libraries location to test/lib
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- Refactor loadDataset function in tests.
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- Remove conditionalEdgeWeights method in BayesMetrics.
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## [1.0.5] 2024-04-20
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### Added
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- Install command and instructions in README.md
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- Prefix to install command to install the package in the any location.
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- The 'block_update' hyperparameter to the BoostAODE class, to control the way weights/significances are updated. Default value is false.
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- Html report of coverage in the coverage folder. It is created with *make viewcoverage*
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- Badges of coverage and code quality (codacy) in README.md. Coverage badge is updated with *make viewcoverage*
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- Tests to reach 97% of coverage.
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- Copyright header to source files.
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- Diagrams to README.md: UML class diagram & dependency diagram
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- Action to create diagrams to Makefile: *make diagrams*
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### Changed
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- Sample app now is a separate target in the Makefile and shows how to use the library with a sample dataset
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- 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.
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- Default hyperparameter values in BoostAODE: bisection is true, maxTolerance is 3, convergence is true
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### Removed
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- The 'predict_single' hyperparameter from the BoostAODE class.
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- The 'repeatSparent' hyperparameter from the BoostAODE class.
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## [1.0.4] 2024-03-06
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### Added
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- Change *ascending* hyperparameter to *order* with these possible values *{"asc", "desc", "rand"}*, Default is *"desc"*.
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- 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.
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- sample app to show how to use the library (make sample)
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### Changed
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- Change the library structure adding folders for each group of classes (classifiers, ensembles, etc).
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- The significances of the models generated under the feature selection algorithm are now computed after all the models have been generated and an α<sub>t</sub> value is computed and assigned to each model.
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## [1.0.3] 2024-02-25
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### Added
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- Voting / probability aggregation in Ensemble classes
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- predict_proba method in Classifier
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- predict_proba method in BoostAODE
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- predict_voting parameter in BoostAODE constructor to use voting or probability to predict (default is voting)
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- hyperparameter predict_voting to AODE, AODELd and BoostAODE (Ensemble child classes)
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- tests to check predict & predict_proba coherence
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## [1.0.2] - 2024-02-20
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### Fixed
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- Fix bug in BoostAODE: do not include the model if epsilon sub t is greater than 0.5
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- Fix bug in BoostAODE: compare accuracy with previous accuracy instead of the first of the ensemble if convergence true
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## [1.0.1] - 2024-02-12
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### Added
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- Notes in Classifier class
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- BoostAODE: Add note with used features in initialization with feature selection
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- BoostAODE: Add note with the number of models
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- BoostAODE: Add note with the number of features used to create models if not all features are used
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- Test version number in TestBayesModels
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- Add tests with feature_select and notes on BoostAODE
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### Fixed
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- Network predict test
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- Network predict_proba test
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- Network score test
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