cargo fmt

examples/regression.rs

@@ -31,8 +31,7 @@ fn main() -> std::io::Result<()> {
         load_file("lightgbm3-sys/lightgbm/examples/regression/regression.test");
     assert_eq!(n_features, n_features_test);
 
-    let train_dataset =
-        Dataset::from_slice(&train_xs, &train_ys, n_features, true).unwrap();
+    let train_dataset = Dataset::from_slice(&train_xs, &train_ys, n_features, true).unwrap();
 
     let params = json! {
         {
@@ -44,12 +43,11 @@ fn main() -> std::io::Result<()> {
 
     // Train a model
     let booster = Booster::train(train_dataset, &params).unwrap();
-    // Predicts floating point 
+    // Predicts floating point
     let y_pred = booster.predict(&test_xs, n_features, true).unwrap();
     // Calculate regression metrics
     let mean = test_ys.iter().sum::<f32>() / test_ys.len() as f32;
-    let var =
-        test_ys.iter().map(|&y| (y - mean).powi(2)).sum::<f32>() / test_ys.len() as f32;
+    let var = test_ys.iter().map(|&y| (y - mean).powi(2)).sum::<f32>() / test_ys.len() as f32;
     let var_model = zip(&test_ys, &y_pred)
         .map(|(&y, &y_pred)| (y - y_pred as f32).powi(2))
         .sum::<f32>()