* 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>
* grid search draft
* hyperparam search for linear estimators
* grid search for ensembles
* support grid search for more algos
* grid search for unsupervised algos
* minor cleanup
* test: run tests also in wasm targets
* fix: install rand with wasm-bindgen por wasm targets
* fix: use actual usize size to access buffer.
* fix: do not run functions that create files in wasm.
* test: do not run in wasm test that panics.
Co-authored-by: Luis Moreno <morenol@users.noreply.github.com>
* feat: Add getters for GaussianNB
* Add classes getter to BernoulliNB
Add classes getter to CategoricalNB
Add classes getter to MultinomialNB
* Add feature_log_prob getter to MultinomialNB
* Add class_count to NB structs
* Add n_features getter for NB
* Add feature_count to MultinomialNB and BernoulliNB
* Add n_categories to CategoricalNB
* Implement feature_log_prob and category_count getter for CategoricalNB
* Implement feature_log_prob for BernoulliNB
* Use log likelihood to make calculations more stable
* Fix problem with class_count in categoricalnb
* Use a similar approach to the one used in scikitlearn to define which are the possible categories of each feature.
