* Implement cosine similarity and cosinepair
* formatting
* fix clippy
* Add top k CosinePair
* fix distance computation
* set min similarity for constant zeros
* bump version to 0.4.5
* refactored decision tree into reusable components
* got rid of api code from base tree because its an implementation detail
* got rid of api code from base tree because its an implementation detail
* changed name
* Fix#245: return error for NaN in naive bayes
* Implement error handling for NaN values in NBayes predict:
* general behaviour has been kept unchanged according to original tests in `mod.rs`
* aka: error is returned only if all the predicted probabilities are NaN
* Add tests
* Add test with static values
* Add test for numerical stability with numpy
* store impurity in the node
* add number of features
* add a TODO
* draft feature importance
* feat
* n_samples of node
* compute_feature_importances
* unit tests
* always calculate impurity
* fix bug
* fix linter
Co-authored-by: Luis Moreno <morenol@users.noreply.github.com>
Co-authored-by: Lorenzo <tunedconsulting@gmail.com>
* Implement rand. Use the new derive [#default]
* Use custom range
* Use range seed
* Bump version
* Add array length checks for
* Handle kernel serialization
* Do not use typetag in WASM
* enable tests for serialization
* Update serde feature deps
Co-authored-by: Luis Moreno <morenol@users.noreply.github.com>
Co-authored-by: Lorenzo <tunedconsulting@gmail.com>
* Fixes for release
* add new test
* Remove change applied in development branch
* Only add dependency for wasm32
* Update ci.yml
Co-authored-by: Luis Moreno <morenol@users.noreply.github.com>
Co-authored-by: Lorenzo <tunedconsulting@gmail.com>
* 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>
