Releases: mlpack/mlpack
Releases · mlpack/mlpack
mlpack 4.6.2
mlpack 4.6.1
mlpack 4.6.0
Released Apr. 3, 2025.
- Fix command-line duplicate output bug when loading matrices for some bindings (#3838).
- Use
CMAKE_BUILD_TYPE
to specify build type instead of DEBUG and PROFILE options (#3865). - Add
MLPACK_NO_STD_MUTEX
to allow disablingstd::mutex
(#3868). - Bundle STB with mlpack and add
ResizeImages()
functionality (#3823). - Add
mlpack.cmake
to facilitate finding mlpack and its dependencies (#3872). - Fix conversion of empty Armadillo objects to numpy in Python bindings (#3896).
- Added bootstrap strategies for
RandomForest
:IdentityBootstrap
,DefaultBootstrap
, andSequentialBootstrap
(#3829). - Add
ResizeCropImages()
for resize-and-crop image preprocessing functionality (#3903). - Fix
LSTM
input size calculation for multidimensional inputs (#3913).
mlpack 4.5.1
Released Dec. 4, 2024.
- Fix compilation with clang 19 (#3799).
- Deprecate version of
data::Split()
that returns astd::tuple
for consistency; use other overloads instead (#3803). - Fix LSTM layer copy/move constructors (#3809).
- Fix compilation if only including
mlpack/methods/kde/kde_model.hpp
(#3800). - Fix serialization and
MinDistance()
bugs withHollowBallBound
(#3808).
mlpack 4.5.0
Released September 18, 2024.
- Distribute STB headers as part of R package (#3724, #3726).
- Added OpenMP parallelization to Hamerly, Naive, and Elkan k-means (#3761, #3762, #3764).
- Added OpenMP support for fast approximation (#3685).
- Implemented the Find and Fill algorithm into the Dropout Layer and added OpenMP support (#3684).
- Update Python bindings to support NumPy 2.x (#3752).
- Bump minimum Armadillo version to 10.8 (#3760).
- Adapt
NearestInterpolation
ANN layer to new Layer Interface (#3768). - Add support for arbitrary matrix types to
Radical
and deprecateRadical::DoRadical()
in favor ofRadical::Apply()
(#3787).
mlpack 4.4.0
Released May 28, 2024.
- Add
print_training_accuracy
option to LogisticRegression bindings (#3552). - Fix
preprocess_split()
call in documentation forLinearRegression
andAdaBoost
Python classes (#3563). - Added
Repeat
ANN layer type (#3565). - Remove
round()
implementation for old MSVC compilers (#3570). - (R) Added inline plugin to the R bindings to allow for other R packages to link to headers (#3626, h/t @cgiachalis).
- (R) Removed extra gcc-specific options from
Makevars.win
(#3627, h/t @kalibera). - (R) Changed roxygen package-level documentation from using
@docType package
to"_PACKAGE"
. (#3636) - Fix floating-point accuracy issue for decision trees that sometimes caused crashes (#3595).
- Use templates metaprog to distinguish between a matrix and a cube type (#3602), (#3585).
- Use
MatType
instead ofarma::Mat<eT>
, (#3567), (#3607), (#3608), (#3609), (#3568). - Generalize matrix operations for armadillo and bandicoot, (#3619), (#3617), (#3610), (#3643), (#3600), (#3605), (#3629).
- Change
arma::conv_to
toConvTo
using a local shim for bandicoot support (#3614). - Fix a bug for the stddev and mean in
RandNormal()
#(3651). - Allow PCA to take different matrix types (#3677).
- Fix usage of precompiled headers; remove cotire (#3635).
- Fix non-working
verbose
option for R bindings (#3691), and add globalmlpack.verbose
option (#3706). - Fix divide-by-zero edge case for LARS (#3701).
- Templatize
SparseCoding
andLocalCoordinateCoding
to allow different matrix types (#3709, #3711). - Fix handling of unused atoms in
LocalCoordinateCoding
(#3711). - Move minimum required C++ version from C++14 to C++17 (#3704).
mlpack 4.3.0
Released Nov. 27, 2023.
- 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
andLayerNorm
ANN layers to new Layer interface (#3547). - Fix inconsistent use of the "input" parameter to the Backward method in ANNs (#3551).
mlpack 4.2.1
Released Sep. 7, 2023. (Sorry for the late Github release. Forgot to hit the "publish" button.)
- 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 toDecisionTree
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 theMLPACK_HAS_STB
macro (#3529).
mlpack 4.2.0
Released June 16, 2023.
- 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 toGaussianInitialization
,LecunNormalInitialization
,KathirvalavakumarSubavathiInitialization
,NguyenWidrowInitialization
, andOrthogonalInitialization
(#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).
mlpack 4.1.0
Released Apr. 27, 2023.
- 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).