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feat: adds serialization/deserialization methods

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This commit is contained in:
Volodymyr Orlov
2020-04-03 11:12:15 -07:00
parent 5766364311
commit eb0c36223f
16 changed files with 555 additions and 159 deletions
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src/cluster/kmeans.rs
+4 -4
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@@ -8,7 +8,7 @@ use serde::{Serialize, Deserialize};
use crate::math::num::FloatExt;
use crate::linalg::Matrix;
use crate::math::distance::euclidian;
use crate::math::distance::euclidian::*;
use crate::algorithm::neighbour::bbd_tree::BBDTree;
#[derive(Serialize, Deserialize, Debug)]
@@ -130,7 +130,7 @@ impl<T: FloatExt + Sum> KMeans<T>{
let mut best_cluster = 0;
for j in 0..self.k {
let dist = euclidian::squared_distance(&x.get_row_as_vec(i), &self.centroids[j]);
let dist = Euclidian::squared_distance(&x.get_row_as_vec(i), &self.centroids[j]);
if dist < min_dist {
min_dist = dist;
best_cluster = j;
@@ -156,7 +156,7 @@ impl<T: FloatExt + Sum> KMeans<T>{
// the distance from each sample to its closest center in scores.
for i in 0..n {
// compute the distance between this sample and the current center
let dist = euclidian::squared_distance(&data.get_row_as_vec(i), &centroid);
let dist = Euclidian::squared_distance(&data.get_row_as_vec(i), &centroid);
if dist < d[i] {
d[i] = dist;
@@ -183,7 +183,7 @@ impl<T: FloatExt + Sum> KMeans<T>{
for i in 0..n {
// compute the distance between this sample and the current center
let dist = euclidian::squared_distance(&data.get_row_as_vec(i), &centroid);
let dist = Euclidian::squared_distance(&data.get_row_as_vec(i), &centroid);
if dist < d[i] {
d[i] = dist;