feat: add Support Vector Classifier (SVC) implementation

Cargo.toml

@@ -9,6 +9,7 @@ num-bigint = { version = "0.4", optional = true }
 num-traits = { version = "0.2", optional = true }
 rand = "0.9"
 nalgebra = "0.34.0"
+ndarray = "0.17.2"
 
 [dev-dependencies]
 quickcheck = "1.0"

DIRECTORY.md

@@ -211,6 +211,7 @@
     * [Naive Bayes](https://github.com/TheAlgorithms/Rust/blob/master/src/machine_learning/naive_bayes.rs)
     * [Perceptron](https://github.com/TheAlgorithms/Rust/blob/master/src/machine_learning/perceptron.rs)
     * [Principal Component Analysis](https://github.com/TheAlgorithms/Rust/blob/master/src/machine_learning/principal_component_analysis.rs)
+    * [Support Vector Classifier](https://github.com/TheAlgorithms/Rust/blob/master/src/machine_learning/support_vector_classifier.rs)
     * Loss Function
       * [Average Margin Ranking Loss](https://github.com/TheAlgorithms/Rust/blob/master/src/machine_learning/loss_function/average_margin_ranking_loss.rs)
       * [Hinge Loss](https://github.com/TheAlgorithms/Rust/blob/master/src/machine_learning/loss_function/hinge_loss.rs)

src/machine_learning/mod.rs

@@ -8,22 +8,19 @@ mod naive_bayes;
 mod optimization;
 mod perceptron;
 mod principal_component_analysis;
+mod support_vector_classifier;
 
 pub use self::cholesky::cholesky;
 pub use self::k_means::k_means;
 pub use self::k_nearest_neighbors::k_nearest_neighbors;
 pub use self::linear_regression::linear_regression;
 pub use self::logistic_regression::logistic_regression;
-pub use self::loss_function::average_margin_ranking_loss;
-pub use self::loss_function::hng_loss;
-pub use self::loss_function::huber_loss;
-pub use self::loss_function::kld_loss;
-pub use self::loss_function::mae_loss;
-pub use self::loss_function::mse_loss;
-pub use self::loss_function::neg_log_likelihood;
+pub use self::loss_function::{
+    average_margin_ranking_loss, hng_loss, huber_loss, kld_loss, mae_loss, mse_loss,
+    neg_log_likelihood,
+};
 pub use self::naive_bayes::naive_bayes;
-pub use self::optimization::gradient_descent;
-pub use self::optimization::Adam;
-pub use self::perceptron::classify;
-pub use self::perceptron::perceptron;
+pub use self::optimization::{gradient_descent, Adam};
+pub use self::perceptron::{classify, perceptron};
 pub use self::principal_component_analysis::principal_component_analysis;
+pub use self::support_vector_classifier::{Kernel, SVCError, SVC};