Mlpack

2023-11-27
* Fix include ordering issue for `LinearRegression` (3541).

* Fix L1 regularization in case where weight is zero (3545).

* Use HTTPS for all auto-downloaded dependencies (3550).

* More robust detection of C++17 mode in the MSVC "compiler" (3555, 3557).

* Fix setting number of classes correctly in `SoftmaxRegression::Train()`
(3553).

* Adapt `MultiheadAttention` and `LayerNorm` ANN layers to new Layer interface
(3547).

* Fix inconsistent use of the "input" parameter to the Backward method in ANNs
(3551).

* Allow passing weak learner hyperparameters directly to AdaBoost (3560).

2023-09-05
* Reinforcement Learning: Gaussian noise (3515).

* Reinforcement Learning: Twin Delayed Deep Deterministic
Policy Gradient (3512).

* Reinforcement Learning: Ornstein-Uhlenbeck noise (3499).

* Reinforcement Learning: Deep Deterministic Policy Gradient (3494).

* Add `ClassProbabilities()` member to `DecisionTree` so that the internal
details of trees can be more easily inspected (3511).

* Bipolar sigmoid activation function added and invertible functions
fixed (3506).

* Add auto-configured `mlpack/config.hpp` to contain configuration details of
mlpack that are required at compile time. STB detection is now done in this
file with the `MLPACK_HAS_STB` macro (3519).

* Fix CRAN package alias for R bindings (3543).

2023-06-14
* Adapt C_ReLU, ReLU6, FlexibleReLU layer for new neural network API (3445).

* Fix PReLU, add integration test to it (3473).

* Fix bug in LogSoftMax derivative (3469).

* Add `serialize` method to `GaussianInitialization`,
`LecunNormalInitialization`,
`KathirvalavakumarSubavathiInitialization`, `NguyenWidrowInitialization`,
and `OrthogonalInitialization` (3483).

* Allow categorical features to `preprocess_one_hot_encode` (3487).

* Install mlpack and cereal headers as part of R package (3488).

* Add intercept and normalization support to LARS (3493).

* Allow adding two features simultaneously to LARS models (3493).

* Adapt FTSwish activation function (3485).

* Adapt Hyper-Sinh activation function (3491).

2023-04-26
* Adapt HardTanH layer (3454).

* Adapt Softmin layer for new neural network API (3437).

* Adapt PReLU layer for new neural network API (3420).

* Add CF decomposition methods: `QUIC_SVDPolicy` and `BlockKrylovSVDPolicy`
(3413, 3404).

* Update outdated code in tutorials (3398, 3401).

* Bugfix for non-square convolution kernels (3376).

* Fix a few missing includes in `<mlpack.hpp>` (3374).

* Fix DBSCAN handling of non-core points (3346).

* Avoid deprecation warnings in Armadillo 11.4.4+ (3405).

* Issue runtime error when serialization of neural networks is attempted but
`MLPACK_ENABLE_ANN_SERIALIZATION` is not defined (3451).

2022-12-23
* Fix mapping of categorical data for Julia bindings (3305).

* Bugfix: catch all exceptions when running bindings from Julia, instead of
crashing (3304).

* Various Python configuration fixes for Windows and OS X (3312, 3313,
3311, 3309, 3308, 3297, 3302).

* Optimize and strip compiled Python bindings when possible, resulting in
significant size minimization (3310).

* The `/std:c++17` and `/Zc:__cplusplus` options are now required when using
Visual Studio (3318). Documentation and compile-time checks added.

* Set `BUILD_TESTS` to `OFF` by default. If you want to build tests, like
`mlpack_test`, manually set `BUILD_TESTS` to `ON` in your CMake
configuration step (3316).

* Fix handling of transposed matrix parameters in Python, Julia, R, and Go
bindings (3327).

* Comment out definition of ARMA_NO DEBUG. This allows various Armadillo
run-time checks such as non-conforming matrices and out-of-bounds
element access. In turn this helps tracking down bugs and incorrect
usage (3322).

2022-10-23
* Bump C++ standard requirement to C++14 (3233).

* Fix `Perceptron` to work with cross-validation framework (3190).

* Migrate from boost tests to Catch2 framework (2523), (2584).

* Bump minimum armadillo version from 8.400 to 9.800 (3043), (3048).

* Adding a copy constructor in the Convolution layer (3067).

* Replace `boost::spirit` parser by a local efficient implementation (2942).

* Disable correctly the autodownloader + fix tests stability (3076).

* Replace `boost::any` with `core::v2::any` or `std::any` if available (3006).

* Remove old non used Boost headers (3005).

* Replace `boost::enable_if` with `std::enable_if` (2998).

* Replace `boost::is_same` with `std::is_same` (2993).

* Remove invalid option for emsmallen and STB (2960).

* Check for armadillo dependencies before downloading armadillo (2954).

* Disable the usage of autodownloader by default (2953).

* Install dependencies downloaded with the autodownloader (2952).

* Download older Boost if the compiler is old (2940).

* Add support for embedded systems (2531).

* Build mlpack executable statically if the library is statically linked (2931).

* Fix cover tree loop bug on embedded arm systems (2869).

* Fix a LAPACK bug in `FindArmadillo.cmake` (2929).

* Add an autodownloader to get mlpack dependencies (2927).

* Remove Coverage files and configurations from CMakeLists (2866).

* Added `Multi Label Soft Margin Loss` loss function for neural networks
(2345).

* Added Decision Tree Regressor (2905). It can be used using the class
`mlpack::tree::DecisionTreeRegressor`. It is accessible only though C++.

* Added dict-style inspection of mlpack models in python bindings (2868).

* Added Extra Trees Algorithm (2883). Currently, it can be used using the
class `mlpack::tree::ExtraTrees`, but only through C++.

* Add Flatten T Swish activation function (`flatten-t-swish.hpp`)

* Added warm start feature to Random Forest (2881); this feature is
accessible from mlpack's bindings to different languages.

* Added Pixel Shuffle layer (2563).

* Add "check_input_matrices" option to python bindings that checks
for NaN and inf values in all the input matrices (2787).

* Add Adjusted R squared functionality to R2Score::Evaluate (2624).

* Disabled all the bindings by default in CMake (2782).

* Added an implementation to Stratify Data (2671).

* Add `BUILD_DOCS` CMake option to control whether Doxygen documentation is
built (default ON) (2730).

* Add Triplet Margin Loss function (2762).

* Add finalizers to Julia binding model types to fix memory handling (2756).

* HMM: add functions to calculate likelihood for data stream with/without
pre-calculated emission probability (2142).

* Replace Boost serialization library with Cereal (2458).

* Add `PYTHON_INSTALL_PREFIX` CMake option to specify installation root for
Python bindings (2797).

* Removed `boost::visitor` from model classes for `knn`, `kfn`, `cf`,
`range_search`, `krann`, and `kde` bindings (2803).

* Add k-means++ initialization strategy (2813).

* `NegativeLogLikelihood<>` now expects classes in the range `0` to
`numClasses - 1` (2534).

* Add `Lambda1()`, `Lambda2()`, `UseCholesky()`, and `Tolerance()` members to
`LARS` so parameters for training can be modified (2861).

* Remove unused `ElemType` template parameter from `DecisionTree` and
`RandomForest` (2874).

* Fix Python binding build when the CMake variable `USE_OPENMP` is set to
`OFF` (2884).

* The `mlpack_test` target is no longer built as part of `make all`. Use
`make mlpack_test` to build the tests.

* Fixes to `HoeffdingTree`: ensure that training still works when empty
constructor is used (2964).

* Fix Julia model serialization bug (2970).

* Fix `LoadCSV()` to use pre-populated `DatasetInfo` objects (2980).

* Add `probabilities` option to softmax regression binding, to get class
probabilities for test points (3001).

* Fix thread safety issues in mlpack bindings to other languages (2995).

* Fix double-free of model pointers in R bindings (3034).

* Fix Julia, Python, R, and Go handling of categorical data for
`decision_tree()` and `hoeffding_tree()` (2971).

* Depend on `pkgbuild` for R bindings (3081).

* Replaced Numpy deprecated code in Python bindings (3126).