feat: consolidates API

src/naive_bayes/gaussian.rs

@@ -22,7 +22,7 @@
 //! let nb = GaussianNB::fit(&x, &y, Default::default()).unwrap();
 //! let y_hat = nb.predict(&x).unwrap();
 //! ```
-use crate::base::Predictor;
+use crate::api::{Predictor, SupervisedEstimator};
 use crate::error::Failed;
 use crate::linalg::row_iter;
 use crate::linalg::BaseVector;
@@ -183,6 +183,14 @@ pub struct GaussianNB<T: RealNumber, M: Matrix<T>> {
     inner: BaseNaiveBayes<T, M, GaussianNBDistribution<T>>,
 }
 
+impl<T: RealNumber, M: Matrix<T>> SupervisedEstimator<M, M::RowVector, GaussianNBParameters<T>>
+    for GaussianNB<T, M>
+{
+    fn fit(x: &M, y: &M::RowVector, parameters: GaussianNBParameters<T>) -> Result<Self, Failed> {
+        GaussianNB::fit(x, y, parameters)
+    }
+}
+
 impl<T: RealNumber, M: Matrix<T>> Predictor<M, M::RowVector> for GaussianNB<T, M> {
     fn predict(&self, x: &M) -> Result<M::RowVector, Failed> {
         self.predict(x)