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>

src/metrics/accuracy.rs

@@ -8,10 +8,20 @@
 //!
 //! ```
 //! use smartcore::metrics::accuracy::Accuracy;
+//! use smartcore::metrics::Metrics;
 //! let y_pred: Vec<f64> = vec![0., 2., 1., 3.];
 //! let y_true: Vec<f64> = vec![0., 1., 2., 3.];
 //!
-//! let score: f64 = Accuracy {}.get_score(&y_pred, &y_true);
+//! let score: f64 = Accuracy::new().get_score(&y_pred, &y_true);
+//! ```
+//! With integers:
+//! ```
+//! use smartcore::metrics::accuracy::Accuracy;
+//! use smartcore::metrics::Metrics;
+//! let y_pred: Vec<i64> = vec![0, 2, 1, 3];
+//! let y_true: Vec<i64> = vec![0, 1, 2, 3];
+//!
+//! let score: f64 = Accuracy::new().get_score(&y_pred, &y_true);
 //! ```
 //!
 //! <script src="https://polyfill.io/v3/polyfill.min.js?features=es6"></script>
@@ -19,37 +29,53 @@
 #[cfg(feature = "serde")]
 use serde::{Deserialize, Serialize};
 
-use crate::linalg::BaseVector;
-use crate::math::num::RealNumber;
+use crate::linalg::basic::arrays::ArrayView1;
+use crate::numbers::basenum::Number;
+use std::marker::PhantomData;
+
+use crate::metrics::Metrics;
 
 /// Accuracy metric.
 #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
 #[derive(Debug)]
-pub struct Accuracy {}
+pub struct Accuracy<T> {
+    _phantom: PhantomData<T>,
+}
 
-impl Accuracy {
+impl<T: Number> Metrics<T> for Accuracy<T> {
+    /// create a typed object to call Accuracy functions
+    fn new() -> Self {
+        Self {
+            _phantom: PhantomData,
+        }
+    }
+    fn new_with(_parameter: f64) -> Self {
+        Self {
+            _phantom: PhantomData,
+        }
+    }
     /// Function that calculated accuracy score.
     /// * `y_true` - cround truth (correct) labels
     /// * `y_pred` - predicted labels, as returned by a classifier.
-    pub fn get_score<T: RealNumber, V: BaseVector<T>>(&self, y_true: &V, y_pred: &V) -> T {
-        if y_true.len() != y_pred.len() {
+    fn get_score(&self, y_true: &dyn ArrayView1<T>, y_pred: &dyn ArrayView1<T>) -> f64 {
+        if y_true.shape() != y_pred.shape() {
             panic!(
                 "The vector sizes don't match: {} != {}",
-                y_true.len(),
-                y_pred.len()
+                y_true.shape(),
+                y_pred.shape()
             );
         }
 
-        let n = y_true.len();
+        let n = y_true.shape();
 
-        let mut positive = 0;
+        let mut positive: i32 = 0;
         for i in 0..n {
-            if y_true.get(i) == y_pred.get(i) {
+            if *y_true.get(i) == *y_pred.get(i) {
                 positive += 1;
             }
         }
 
-        T::from_i64(positive).unwrap() / T::from_usize(n).unwrap()
+        positive as f64 / n as f64
     }
 }
 
@@ -59,14 +85,27 @@ mod tests {
 
     #[cfg_attr(target_arch = "wasm32", wasm_bindgen_test::wasm_bindgen_test)]
     #[test]
-    fn accuracy() {
+    fn accuracy_float() {
         let y_pred: Vec<f64> = vec![0., 2., 1., 3.];
         let y_true: Vec<f64> = vec![0., 1., 2., 3.];
 
-        let score1: f64 = Accuracy {}.get_score(&y_pred, &y_true);
-        let score2: f64 = Accuracy {}.get_score(&y_true, &y_true);
+        let score1: f64 = Accuracy::<f64>::new().get_score(&y_pred, &y_true);
+        let score2: f64 = Accuracy::<f64>::new().get_score(&y_true, &y_true);
 
         assert!((score1 - 0.5).abs() < 1e-8);
         assert!((score2 - 1.0).abs() < 1e-8);
     }
+
+    #[cfg_attr(target_arch = "wasm32", wasm_bindgen_test::wasm_bindgen_test)]
+    #[test]
+    fn accuracy_int() {
+        let y_pred: Vec<i32> = vec![0, 2, 1, 3];
+        let y_true: Vec<i32> = vec![0, 1, 2, 3];
+
+        let score1: f64 = Accuracy::<i32>::new().get_score(&y_pred, &y_true);
+        let score2: f64 = Accuracy::<i32>::new().get_score(&y_true, &y_true);
+
+        assert_eq!(score1, 0.5);
+        assert_eq!(score2, 1.0);
+    }
 }