feat: documents ensemble models

src/math/distance/euclidian.rs

@@ -16,7 +16,8 @@
 //! let l2: f64 = Euclidian{}.distance(&x, &y);
 //! ```
 //!
-//! <script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-AMS_CHTML"></script>
+//! <script src="https://polyfill.io/v3/polyfill.min.js?features=es6"></script>
+//! <script id="MathJax-script" async src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js"></script>
 use serde::{Deserialize, Serialize};
 
 use crate::math::num::RealNumber;

src/math/distance/hamming.rs

@@ -16,7 +16,8 @@
 //!
 //! ```
 //!
-//! <script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-AMS_CHTML"></script>
+//! <script src="https://polyfill.io/v3/polyfill.min.js?features=es6"></script>
+//! <script id="MathJax-script" async src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js"></script>
 
 use serde::{Deserialize, Serialize};
 

src/math/distance/mahalanobis.rs

@@ -38,7 +38,8 @@
 //! * ["Introduction to Multivariate Statistical Analysis in Chemometrics", Varmuza, K., Filzmoser, P., 2016, p.46](https://www.taylorfrancis.com/books/9780429145049)
 //! * ["Example of Calculating the Mahalanobis Distance", McCaffrey, J.D.](https://jamesmccaffrey.wordpress.com/2017/11/09/example-of-calculating-the-mahalanobis-distance/)
 //!
-//! <script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-AMS_CHTML"></script>
+//! <script src="https://polyfill.io/v3/polyfill.min.js?features=es6"></script>
+//! <script id="MathJax-script" async src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js"></script>
 #![allow(non_snake_case)]
 
 use std::marker::PhantomData;

src/math/distance/manhattan.rs

@@ -15,7 +15,8 @@
 //!
 //! let l1: f64 = Manhattan {}.distance(&x, &y);
 //! ```
-//! <script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-AMS_CHTML"></script>
+//! <script src="https://polyfill.io/v3/polyfill.min.js?features=es6"></script>
+//! <script id="MathJax-script" async src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js"></script>
 use serde::{Deserialize, Serialize};
 
 use crate::math::num::RealNumber;

src/math/distance/minkowski.rs

@@ -18,7 +18,8 @@
 //! let l2: f64 = Minkowski { p: 2 }.distance(&x, &y);
 //!
 //! ```
-//! <script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-AMS_CHTML"></script>
+//! <script src="https://polyfill.io/v3/polyfill.min.js?features=es6"></script>
+//! <script id="MathJax-script" async src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js"></script>
 
 use serde::{Deserialize, Serialize};
 

src/math/distance/mod.rs

@@ -10,7 +10,8 @@
 //!
 //! A good distance metric helps to improve the performance of classification, clustering and information retrieval algorithms significantly.
 //!
-//! <script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-AMS_CHTML"></script>
+//! <script src="https://polyfill.io/v3/polyfill.min.js?features=es6"></script>
+//! <script id="MathJax-script" async src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js"></script>
 
 /// Euclidean Distance is the straight-line distance between two points in Euclidean spacere that presents the shortest distance between these points.
 pub mod euclidian;