fmt

Dcyaprogrammer · Dcyaprogrammer · commit cb1e2f91a9fe · 2026-01-16T23:43:15.000+08:00
diff --git a/src/machine_learning/naive_bayes.rs b/src/machine_learning/naive_bayes.rs
@@ -74,7 +74,6 @@ fn gaussian_log_pdf(x: f64, mean: f64, variance: f64) -> f64 {
     log_coefficient + exponent_term
 }
 
-
 pub fn train_naive_bayes(training_data: Vec<(Vec<f64>, f64)>) -> Option<Vec<ClassStatistics>> {
     if training_data.is_empty() {
         return None;
@@ -122,7 +121,6 @@ pub fn train_naive_bayes(training_data: Vec<(Vec<f64>, f64)>) -> Option<Vec<Clas
     Some(class_stats)
 }
 
-
 pub fn predict_naive_bayes(model: &[ClassStatistics], test_point: &[f64]) -> Option<f64> {
     if model.is_empty() || test_point.is_empty() {
         return None;
@@ -158,7 +156,6 @@ pub fn predict_naive_bayes(model: &[ClassStatistics], test_point: &[f64]) -> Opt
     best_class
 }
 
-
 pub fn naive_bayes(training_data: Vec<(Vec<f64>, f64)>, test_point: Vec<f64>) -> Option<f64> {
     let model = train_naive_bayes(training_data)?;
     predict_naive_bayes(&model, &test_point)

Original file line number	Diff line number	Diff line change
`@@ -74,7 +74,6 @@ fn gaussian_log_pdf(x: f64, mean: f64, variance: f64) -> f64 {`
`74`	`74`	`log_coefficient + exponent_term`
`75`	`75`	`}`
`76`	`76`
`77`		`-`
`78`	`77`	`pub fn train_naive_bayes(training_data: Vec<(Vec<f64>, f64)>) -> Option<Vec<ClassStatistics>> {`
`79`	`78`	`if training_data.is_empty() {`
`80`	`79`	`return None;`
`@@ -122,7 +121,6 @@ pub fn train_naive_bayes(training_data: Vec<(Vec<f64>, f64)>) -> Option<Vec<Clas`
`122`	`121`	`Some(class_stats)`
`123`	`122`	`}`
`124`	`123`
`125`		`-`
`126`	`124`	`pub fn predict_naive_bayes(model: &[ClassStatistics], test_point: &[f64]) -> Option<f64> {`
`127`	`125`	`if model.is_empty() \|\| test_point.is_empty() {`
`128`	`126`	`return None;`
`@@ -158,7 +156,6 @@ pub fn predict_naive_bayes(model: &[ClassStatistics], test_point: &[f64]) -> Opt`
`158`	`156`	`best_class`
`159`	`157`	`}`
`160`	`158`
`161`		`-`
`162`	`159`	`pub fn naive_bayes(training_data: Vec<(Vec<f64>, f64)>, test_point: Vec<f64>) -> Option<f64> {`
`163`	`160`	`let model = train_naive_bayes(training_data)?;`
`164`	`161`	`predict_naive_bayes(&model, &test_point)`