Merge potential next release v0.4 (#187) Breaking Changes
* 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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+22
-15
@@ -19,11 +19,17 @@ use crate::dataset::deserialize_data;
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use crate::dataset::Dataset;
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/// Get dataset
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pub fn load_dataset() -> Dataset<f32, f32> {
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let (x, y, num_samples, num_features) = match deserialize_data(std::include_bytes!("iris.xy")) {
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Err(why) => panic!("Can't deserialize iris.xy. {}", why),
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Ok((x, y, num_samples, num_features)) => (x, y, num_samples, num_features),
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};
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pub fn load_dataset() -> Dataset<f32, u32> {
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let (x, y, num_samples, num_features): (Vec<f32>, Vec<u32>, usize, usize) =
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match deserialize_data(std::include_bytes!("iris.xy")) {
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Err(why) => panic!("Can't deserialize iris.xy. {}", why),
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Ok((x, y, num_samples, num_features)) => (
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x,
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y.into_iter().map(|x| x as u32).collect(),
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num_samples,
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num_features,
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),
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};
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Dataset {
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data: x,
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@@ -50,18 +56,19 @@ pub fn load_dataset() -> Dataset<f32, f32> {
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#[cfg(test)]
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mod tests {
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#[cfg(not(target_arch = "wasm32"))]
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use super::super::*;
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// #[cfg(not(target_arch = "wasm32"))]
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// use super::super::*;
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use super::*;
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#[cfg(not(target_arch = "wasm32"))]
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#[test]
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#[ignore]
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fn refresh_iris_dataset() {
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// run this test to generate iris.xy file.
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let dataset = load_dataset();
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assert!(serialize_data(&dataset, "iris.xy").is_ok());
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}
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// TODO: fix serialization
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// #[cfg(not(target_arch = "wasm32"))]
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// #[test]
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// #[ignore]
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// fn refresh_iris_dataset() {
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// // run this test to generate iris.xy file.
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// let dataset = load_dataset();
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// assert!(serialize_data(&dataset, "iris.xy").is_ok());
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// }
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#[cfg_attr(target_arch = "wasm32", wasm_bindgen_test::wasm_bindgen_test)]
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#[test]
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