feat: adds KNN Regressor

src/neighbors/mod.rs

@@ -1 +1,47 @@
-pub mod knn;
+//! # Nearest Neighbors
+
+use serde::{Deserialize, Serialize};
+use crate::algorithm::neighbour::cover_tree::CoverTree;
+use crate::algorithm::neighbour::linear_search::LinearKNNSearch;
+use crate::math::distance::Distance;
+use crate::math::num::FloatExt;
+
+/// 
+pub mod knn_classifier;
+pub mod knn_regressor;
+
+#[derive(Serialize, Deserialize, Debug)]
+pub enum KNNAlgorithmName {
+    LinearSearch,
+    CoverTree,
+}
+
+#[derive(Serialize, Deserialize, Debug)]
+enum KNNAlgorithm<T: FloatExt, D: Distance<Vec<T>, T>> {
+    LinearSearch(LinearKNNSearch<Vec<T>, T, D>),
+    CoverTree(CoverTree<Vec<T>, T, D>),
+}
+
+impl KNNAlgorithmName {
+    fn fit<T: FloatExt, D: Distance<Vec<T>, T>>(
+        &self,
+        data: Vec<Vec<T>>,
+        distance: D,
+    ) -> KNNAlgorithm<T, D> {
+        match *self {
+            KNNAlgorithmName::LinearSearch => {
+                KNNAlgorithm::LinearSearch(LinearKNNSearch::new(data, distance))
+            }
+            KNNAlgorithmName::CoverTree => KNNAlgorithm::CoverTree(CoverTree::new(data, distance)),
+        }
+    }
+}
+
+impl<T: FloatExt, D: Distance<Vec<T>, T>> KNNAlgorithm<T, D> {
+    fn find(&self, from: &Vec<T>, k: usize) -> Vec<usize> {
+        match *self {
+            KNNAlgorithm::LinearSearch(ref linear) => linear.find(from, k),
+            KNNAlgorithm::CoverTree(ref cover) => cover.find(from, k),
+        }
+    }
+}