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* First draft of the new n-dimensional arrays + NB use case * Improves default implementation of multiple Array methods * Refactors tree methods * Adds matrix decomposition routines * Adds matrix decomposition methods to ndarray and nalgebra bindings * Refactoring + linear regression now uses array2 * Ridge & Linear regression * LBFGS optimizer & logistic regression * LBFGS optimizer & logistic regression * Changes linear methods, metrics and model selection methods to new n-dimensional arrays * Switches KNN and clustering algorithms to new n-d array layer * Refactors distance metrics * Optimizes knn and clustering methods * Refactors metrics module * Switches decomposition methods to n-dimensional arrays * Linalg refactoring - cleanup rng merge (#172) * Remove legacy DenseMatrix and BaseMatrix implementation. Port the new Number, FloatNumber and Array implementation into module structure. * Exclude AUC metrics. Needs reimplementation * Improve developers walkthrough New traits system in place at `src/numbers` and `src/linalg` Co-authored-by: Lorenzo <tunedconsulting@gmail.com> * Provide SupervisedEstimator with a constructor to avoid explicit dynamical box allocation in 'cross_validate' and 'cross_validate_predict' as required by the use of 'dyn' as per Rust 2021 * Implement getters to use as_ref() in src/neighbors * Implement getters to use as_ref() in src/naive_bayes * Implement getters to use as_ref() in src/linear * Add Clone to src/naive_bayes * Change signature for cross_validate and other model_selection functions to abide to use of dyn in Rust 2021 * Implement ndarray-bindings. Remove FloatNumber from implementations * Drop nalgebra-bindings support (as decided in conf-call to go for ndarray) * Remove benches. Benches will have their own repo at smartcore-benches * Implement SVC * Implement SVC serialization. Move search parameters in dedicated module * Implement SVR. Definitely too slow * Fix compilation issues for wasm (#202) Co-authored-by: Luis Moreno <morenol@users.noreply.github.com> * Fix tests (#203) * Port linalg/traits/stats.rs * Improve methods naming * Improve Display for DenseMatrix Co-authored-by: Montana Low <montanalow@users.noreply.github.com> Co-authored-by: VolodymyrOrlov <volodymyr.orlov@gmail.com>
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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
- Seeds to multiple algorithims that depend on random number generation.
- Added feature
jsto use WASM in browser - Drop
nalgebra-bindingsfeature - Complete refactoring with extensive API changes that includes:
- moving to a new traits system, less structs more traits
- adapting all the modules to the new traits system
- moving towards Rust 2021, in particular the use of
dynandas_ref - reorganization of the code base, trying to eliminate duplicates
BREAKING CHANGE
- Added a new parameter to
train_test_splitto define the seed.
[0.2.1] - 2022-05-10
Added
- L2 regularization penalty to the Logistic Regression
- Getters for the naive bayes structs
- One hot encoder
- Make moons data generator
- Support for WASM.
Changed
- Make serde optional
[0.2.0] - 2021-01-03
Added
- DBSCAN
- Epsilon-SVR, SVC
- Ridge, Lasso, ElasticNet
- Bernoulli, Gaussian, Categorical and Multinomial Naive Bayes
- K-fold Cross Validation
- Singular value decomposition
- New api module
- Integration with Clippy
- Cholesky decomposition
Changed
- ndarray upgraded to 0.14
- smartcore::error:FailedError is now non-exhaustive
- K-Means
- PCA
- Random Forest
- Linear and Logistic Regression
- KNN
- Decision Tree
[0.1.0] - 2020-09-25
Added
- First release of smartcore.
- KNN + distance metrics (Euclidian, Minkowski, Manhattan, Hamming, Mahalanobis)
- Linear Regression (OLS)
- Logistic Regression
- Random Forest Classifier
- Decision Tree Classifier
- PCA
- K-Means
- Integrated with ndarray
- Abstract linear algebra methods
- RandomForest Regressor
- Decision Tree Regressor
- Serde integration
- Integrated with nalgebra
- LU, QR, SVD, EVD
- Evaluation Metrics