From 763a8370ebf4fbc513ac3ff6c032f877ac8fcad2 Mon Sep 17 00:00:00 2001
From: Luis Moreno <morenol@users.noreply.github.com>
Date: Sat, 5 Jun 2021 00:25:34 -0400
Subject: [PATCH 1/2] docs: fix documentation of naive bayes structs

---
 src/naive_bayes/bernoulli.rs   | 3 ++-
 src/naive_bayes/gaussian.rs    | 5 +++--
 src/naive_bayes/multinomial.rs | 2 +-
 3 files changed, 6 insertions(+), 4 deletions(-)

diff --git a/src/naive_bayes/bernoulli.rs b/src/naive_bayes/bernoulli.rs
index 69eb13c..95c4d36 100644
--- a/src/naive_bayes/bernoulli.rs
+++ b/src/naive_bayes/bernoulli.rs
@@ -249,7 +249,8 @@ impl<T: RealNumber> BernoulliNBDistribution<T> {
     }
 }
 
-/// BernoulliNB implements the categorical naive Bayes algorithm for categorically distributed data.
+/// BernoulliNB implements the naive Bayes algorithm for data that follows the Bernoulli
+/// distribution.
 #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
 #[derive(Debug, PartialEq)]
 pub struct BernoulliNB<T: RealNumber, M: Matrix<T>> {
diff --git a/src/naive_bayes/gaussian.rs b/src/naive_bayes/gaussian.rs
index b84e65f..bd23919 100644
--- a/src/naive_bayes/gaussian.rs
+++ b/src/naive_bayes/gaussian.rs
@@ -33,7 +33,7 @@ use crate::naive_bayes::{BaseNaiveBayes, NBDistribution};
 #[cfg(feature = "serde")]
 use serde::{Deserialize, Serialize};
 
-/// Naive Bayes classifier for categorical features
+/// Naive Bayes classifier using Gaussian distribution
 #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
 #[derive(Debug, PartialEq)]
 struct GaussianNBDistribution<T: RealNumber> {
@@ -179,7 +179,8 @@ impl<T: RealNumber> GaussianNBDistribution<T> {
     }
 }
 
-/// GaussianNB implements the categorical naive Bayes algorithm for categorically distributed data.
+/// GaussianNB implements the naive Bayes algorithm for data that follows the Gaussian
+/// distribution.
 #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
 #[derive(Debug, PartialEq)]
 pub struct GaussianNB<T: RealNumber, M: Matrix<T>> {
diff --git a/src/naive_bayes/multinomial.rs b/src/naive_bayes/multinomial.rs
index 43a022a..f42b99e 100644
--- a/src/naive_bayes/multinomial.rs
+++ b/src/naive_bayes/multinomial.rs
@@ -212,7 +212,7 @@ impl<T: RealNumber> MultinomialNBDistribution<T> {
     }
 }
 
-/// MultinomialNB implements the categorical naive Bayes algorithm for categorically distributed data.
+/// MultinomialNB implements the naive Bayes algorithm for multinomially distributed data.
 #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
 #[derive(Debug, PartialEq)]
 pub struct MultinomialNB<T: RealNumber, M: Matrix<T>> {

From 0b3bf946dfc40153b910e61a05de6dd90c95b6d7 Mon Sep 17 00:00:00 2001
From: Luis Moreno <morenol@users.noreply.github.com>
Date: Sat, 5 Jun 2021 01:00:38 -0400
Subject: [PATCH 2/2] chore: fix clippy warnings

---
 src/linalg/evd.rs                   | 2 +-
 src/linalg/ndarray_bindings.rs      | 2 +-
 src/naive_bayes/categorical.rs      | 2 +-
 src/preprocessing/series_encoder.rs | 6 ++----
 4 files changed, 5 insertions(+), 7 deletions(-)

diff --git a/src/linalg/evd.rs b/src/linalg/evd.rs
index 78b6cc2..81e2315 100644
--- a/src/linalg/evd.rs
+++ b/src/linalg/evd.rs
@@ -93,7 +93,7 @@ pub trait EVDDecomposableMatrix<T: RealNumber>: BaseMatrix<T> {
             sort(&mut d, &mut e, &mut V);
         }
 
-        Ok(EVD { V, d, e })
+        Ok(EVD { d, e, V })
     }
 }
 
diff --git a/src/linalg/ndarray_bindings.rs b/src/linalg/ndarray_bindings.rs
index 0aa97aa..e081dcc 100644
--- a/src/linalg/ndarray_bindings.rs
+++ b/src/linalg/ndarray_bindings.rs
@@ -966,7 +966,7 @@ mod tests {
         let error: f64 = y
             .into_iter()
             .zip(y_hat.into_iter())
-            .map(|(&a, &b)| (a - b).abs())
+            .map(|(a, b)| (a - b).abs())
             .sum();
 
         assert!(error <= 1.0);
diff --git a/src/naive_bayes/categorical.rs b/src/naive_bayes/categorical.rs
index 51619b6..44e5dd9 100644
--- a/src/naive_bayes/categorical.rs
+++ b/src/naive_bayes/categorical.rs
@@ -232,8 +232,8 @@ impl<T: RealNumber> CategoricalNBDistribution<T> {
             class_labels,
             class_priors,
             coefficients,
-            n_categories,
             n_features,
+            n_categories,
             category_count,
         })
     }
diff --git a/src/preprocessing/series_encoder.rs b/src/preprocessing/series_encoder.rs
index 2cd4133..ab99b08 100644
--- a/src/preprocessing/series_encoder.rs
+++ b/src/preprocessing/series_encoder.rs
@@ -134,10 +134,8 @@ where
         U: RealNumber,
         V: BaseVector<U>,
     {
-        match self.get_num(category) {
-            None => None,
-            Some(&idx) => Some(make_one_hot::<U, V>(idx, self.num_categories)),
-        }
+        self.get_num(category)
+            .map(|&idx| make_one_hot::<U, V>(idx, self.num_categories))
     }
 
     /// Invert one-hot vector, back to the category