feat: adds 3 new regression metrics

src/metrics/r2.rs

@@ -0,0 +1,58 @@
+use serde::{Deserialize, Serialize};
+
+use crate::linalg::BaseVector;
+use crate::math::num::FloatExt;
+
+#[derive(Serialize, Deserialize, Debug)]
+pub struct R2 {}
+
+impl R2 {
+    pub fn get_score<T: FloatExt, V: BaseVector<T>>(&self, y_true: &V, y_pred: &V) -> T {
+        if y_true.len() != y_pred.len() {
+            panic!(
+                "The vector sizes don't match: {} != {}",
+                y_true.len(),
+                y_pred.len()
+            );
+        }
+
+        let n = y_true.len();
+
+        let mut mean = T::zero();
+
+        for i in 0..n {
+            mean = mean + y_true.get(i);
+        }
+
+        mean = mean / T::from_usize(n).unwrap();
+
+        let mut ss_tot = T::zero();
+        let mut ss_res = T::zero();
+
+        for i in 0..n {
+            let y_i = y_true.get(i);
+            let f_i = y_pred.get(i);
+            ss_tot = ss_tot + (y_i - mean).square();
+            ss_res = ss_res + (y_i - f_i).square();
+        }
+
+        T::one() - (ss_res / ss_tot)
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn r2() {
+        let y_true: Vec<f64> = vec![3., -0.5, 2., 7.];
+        let y_pred: Vec<f64> = vec![2.5, 0.0, 2., 8.];
+
+        let score1: f64 = R2 {}.get_score(&y_true, &y_pred);
+        let score2: f64 = R2 {}.get_score(&y_true, &y_true);
+
+        assert!((score1 - 0.948608137).abs() < 1e-8);
+        assert!((score2 - 1.0).abs() < 1e-8);
+    }
+}