feat: refactors packages layout

src/classification/mod.rs

@@ -1,23 +0,0 @@
-use crate::common::Nominal;
-
-pub mod knn;
-pub mod logistic_regression;
-pub mod decision_tree;
-pub mod random_forest;
-
-pub trait Classifier<X, Y>
-where 
-    Y: Nominal
-{    
-
-    fn predict(&self, x: &X) -> Y;
-
-    fn predict_vec(&self, x: &Vec<X>) -> Vec<Y>{
-        let mut result = Vec::new();        
-        for xv in x.iter() {
-            result.push(self.predict(xv));
-        }          
-        result
-    }
-
-}

src/ensemble/mod.rs

@@ -0,0 +1 @@
+pub mod random_forest;

src/ensemble/random_forest.rs

@@ -3,7 +3,7 @@ extern crate rand;
 use rand::Rng;
 use std::default::Default;
 use crate::linalg::Matrix;
-use crate::classification::decision_tree::{DecisionTree, DecisionTreeParameters, SplitCriterion, which_max};
+use crate::tree::decision_tree::{DecisionTree, DecisionTreeParameters, SplitCriterion, which_max};
 
 #[derive(Debug, Clone)]
 pub struct RandomForestParameters {  

src/lib.rs

@@ -1,5 +1,7 @@
-pub mod classification;
-pub mod regression;
+pub mod linear;
+pub mod neighbors;
+pub mod ensemble;
+pub mod tree;
 pub mod cluster;
 pub mod decomposition;
 pub mod linalg;

src/linear/mod.rs

@@ -0,0 +1,2 @@
+pub mod linear_regression;
+pub mod logistic_regression;

src/neighbors/mod.rs

@@ -0,0 +1 @@
+pub mod knn;

src/regression/mod.rs

@@ -1 +0,0 @@
-pub mod linear_regression;

src/tree/mod.rs

@@ -0,0 +1 @@
+pub mod decision_tree;