feat: expose hyper tuning module in model_selection (#179)

* feat: expose hyper tuning module in model_selection

* Move to a folder

Co-authored-by: Luis Moreno <morenol@users.noreply.github.com>

src/model_selection/hyper_tuning/grid_search.rs

@@ -1,3 +1,12 @@
+use crate::{
+    api::Predictor,
+    error::{Failed, FailedError},
+    linalg::Matrix,
+    math::num::RealNumber,
+};
+
+use crate::model_selection::{cross_validate, BaseKFold, CrossValidationResult};
+
 /// grid search results.
 #[derive(Clone, Debug)]
 pub struct GridSearchResult<T: RealNumber, I: Clone> {
@@ -60,8 +69,11 @@ where
 
 #[cfg(test)]
 mod tests {
-  use crate::linear::logistic_regression::{
+    use crate::{
-    LogisticRegression, LogisticRegressionSearchParameters,
+        linalg::naive::dense_matrix::DenseMatrix,
+        linear::logistic_regression::{LogisticRegression, LogisticRegressionSearchParameters},
+        metrics::accuracy,
+        model_selection::{hyper_tuning::grid_search, KFold},
     };
 
     #[test]

src/model_selection/hyper_tuning/mod.rs

@@ -0,0 +1,2 @@
+mod grid_search;
+pub use grid_search::{grid_search, GridSearchResult};

src/model_selection/mod.rs

@@ -110,8 +110,10 @@ use crate::math::num::RealNumber;
 use crate::rand::get_rng_impl;
 use rand::seq::SliceRandom;
 
+pub(crate) mod hyper_tuning;
 pub(crate) mod kfold;
 
+pub use hyper_tuning::{grid_search, GridSearchResult};
 pub use kfold::{KFold, KFoldIter};
 
 /// An interface for the K-Folds cross-validator