Mlpack

_2020-06-18_

* Added Noisy DQN to q_networks (2446).

* Add Go bindings (1884).

* Added Dueling DQN to q_networks, Noisy linear layer to ann/layer
and Empty loss to ann/loss_functions (2414).

* Storing and adding accessor method for action in q_learning (2413).

* Added accessor methods for ANN layers (2321).

* Addition of `Elliot` activation function (2268).

* Add adaptive max pooling and adaptive mean pooling layers (2195).

* Add parameter to avoid shuffling of data in preprocess_split (2293).

* Add `MatType` parameter to `LSHSearch`, allowing sparse matrices to be used
for search (2395).

* Documentation fixes to resolve Doxygen warnings and issues (2400).

* Add Load and Save of Sparse Matrix (2344).

* Add Intersection over Union (IoU) metric for bounding boxes (2402).

* Add Non Maximal Supression (NMS) metric for bounding boxes (2410).

* Fix `no_intercept` and probability computation for linear SVM bindings
(2419).

* Fix incorrect neighbors for `k > 1` searches in `approx_kfn` binding, for
the `QDAFN` algorithm (2448).

* Fix serialization of kernels with state for FastMKS (2452).

* Add `RBF` layer in ann module to make `RBFN` architecture (2261).

_2020-04-29_

* Minor Julia and Python documentation fixes (2373).

* Updated terminal state and fixed bugs for Pendulum environment (2354,
2369).

* Added `EliSH` activation function (2323).

* Add L1 Loss function (2203).

* Pass CMAKE_CXX_FLAGS (compilation options) correctly to Python build
(2367).

* Expose ensmallen Callbacks for sparseautoencoder (2198).

* Bugfix for LARS class causing invalid read (2374).

* Add serialization support from Julia; use `mlpack.serialize()` and
`mlpack.deserialize()` to save and load from `IOBuffer`s.

_2020-04-07_

* Added `Normal Distribution` to `ann/dists` (2382).

* Templated return type of `Forward function` of loss functions (2339).

* Added `R2 Score` regression metric (2323).

* Added `poisson negative log likelihood` loss function (2196).

* Added `huber` loss function (2199).

* Added `mean squared logarithmic error` loss function for neural networks
(2210).

* Added `mean bias loss function` for neural networks (2210).

* The DecisionStump class has been marked deprecated; use the `DecisionTree`
class with `NoRecursion=true` or use `ID3DecisionStump` instead (2099).

* Added `probabilities_file` parameter to get the probabilities matrix of
AdaBoost classifier (2050).

* Fix STB header search paths (2104).

* Add `DISABLE_DOWNLOADS` CMake configuration option (2104).

* Add padding layer in TransposedConvolutionLayer (2082).

* Fix pkgconfig generation on non-Linux systems (2101).

* Use log-space to represent HMM initial state and transition probabilities
(2081).

* Add functions to access parameters of `Convolution` and `AtrousConvolution`
layers (1985).

* Add Compute Error function in lars regression and changing Train function to
return computed error (2139).

* Add Julia bindings (1949). Build settings can be controlled with the
`BUILD_JULIA_BINDINGS=(ON/OFF)` and `JULIA_EXECUTABLE=/path/to/julia` CMake
parameters.

* CMake fix for finding STB include directory (2145).

* Add bindings for loading and saving images (2019); `mlpack_image_converter`
from the command-line, `mlpack.image_converter()` from Python.

* Add normalization support for CF binding (2136).

* Add Mish activation function (2158).

* Update `init_rules` in AMF to allow users to merge two initialization
rules (2151).

* Add GELU activation function (2183).

* Better error handling of eigendecompositions and Cholesky decompositions
(2088, 1840).

* Add LiSHT activation function (2182).

* Add Valid and Same Padding for Transposed Convolution layer (2163).

* Add CELU activation function (2191)

* Add Log-Hyperbolic-Cosine Loss function (2207).

* Change neural network types to avoid unnecessary use of rvalue references
(2259).

* Bump minimum Boost version to 1.58 (2305).

* Refactor STB support so `HAS_STB` macro is not needed when compiling against
mlpack (2312).

* Add Hard Shrink Activation Function (2186).

* Add Soft Shrink Activation Function (2174).

* Add Hinge Embedding Loss Function (2229).

* Add Cosine Embedding Loss Function (2209).

* Add Margin Ranking Loss Function (2264).

* Bugfix for incorrect parameter vector sizes in logistic regression and
softmax regression (2359).

_2019-11-26_

* Add `valid` and `same` padding option in `Convolution` and `Atrous
Convolution` layer (1988).

* Add Model() to the FFN class to access individual layers (2043).

* Update documentation for pip and conda installation packages (2044).

* Add bindings for linear SVM (1935); `mlpack_linear_svm` from the
command-line, `linear_svm()` from Python.

* Add support to return the layer name as `std::string` (1987).

* Speed and memory improvements for the Transposed Convolution layer (1493).

* Fix Windows Python build configuration (1885).

* Validate md5 of STB library after download (2087).

* Add `__version__` to `__init__.py` (2092).

* Correctly handle RNN sequences that are shorter than the value of rho (2102).

_2019-10-01_

* Enforce CMake version check for ensmallen (2032).

* Fix CMake check for Armadillo version (2029).

* Better handling of when STB is not installed (2033).

* Fix Naive Bayes classifier computations in high dimensions (2022).

_2019-09-25_

* Fix some potential infinity errors in Naive Bayes Classifier (2022).

* Fix occasionally-failing RADICAL test (1924).

* Fix gcc 9 OpenMP compilation issue (1970).

* Added support for loading and saving of images (1903).

* Add Multiple Pole Balancing Environment (1901, 1951).

* Added functionality for scaling of data (1876); see the command-line
binding `mlpack_preprocess_scale` or Python binding `preprocess_scale()`.

* Add new parameter `maximum_depth` to decision tree and random forest
bindings (1916).

* Fix prediction output of softmax regression when test set accuracy is
calculated (1922).

* Pendulum environment now checks for termination. All RL environments now
have an option to terminate after a set number of time steps (no limit
by default) (1941).

* Add support for probabilistic KDE (kernel density estimation) error bounds
when using the Gaussian kernel (1934).

* Fix negative distances for cover tree computation (1979).

* Fix cover tree building when all pairwise distances are 0 (1986).

* Improve KDE pruning by reclaiming not used error tolerance (1954, 1984).

* Optimizations for sparse matrix accesses in z-score normalization for CF
(1989).

* Add `kmeans_max_iterations` option to GMM training binding `gmm_train_main`.

* Bump minimum Armadillo version to 8.400.0 due to ensmallen dependency
requirement (2015).