ml-kmeans - npm Package Compare versions

Comparing version 4.0.0 to 4.0.1

History.md

@@ -0,1 +1,11 @@
+<a name="4.0.1"></a>
+## [4.0.1](https://github.com/mljs/kmeans/compare/v4.0.0...v4.0.1) (2018-05-24)
+
+
+### Bug Fixes
+
+* keep initial value for empty centroids ([94b0de9](https://github.com/mljs/kmeans/commit/94b0de9))
+
+
+
 <a name="4.0.0"></a>
@@ -2,0 +12,0 @@ # [4.0.0](https://github.com/mljs/kmeans/compare/v3.1.0...v4.0.0) (2018-05-23)

kmeans.js

@@ -57,2 +57,3 @@ 'use strict';
  * @ignore
+ * @param {Array<Array<number>>} prevCenters - Centroids from the previous iteration
  * @param {Array <Array <number>>} data - the [x,y,z,...] points to cluster
@@ -63,6 +64,6 @@ * @param {Array <number>} clusterID - the cluster identifier for each data dot
  */
-function updateCenters(data, clusterID, K) {
+function updateCenters(prevCenters, data, clusterID, K) {
   const nDim = data[0].length;
 
-  // creates empty centers with 0 size
+  // copy previous centers
   var centers = new Array(K);
@@ -89,3 +90,7 @@ var centersLen = new Array(K);
     for (var d = 0; d < nDim; d++) {
-      centers[id][d] /= centersLen[id];
+      if (centersLen[id]) {
+        centers[id][d] /= centersLen[id];
+      } else {
+        centers[id][d] = prevCenters[id][d];
+      }
     }
@@ -325,3 +330,7 @@ }
     for (var j = 0; j < this.centroids.length; j++) {
-      enrichedCentroids[j].error /= enrichedCentroids[j].size;
+      if (enrichedCentroids[j].size) {
+        enrichedCentroids[j].error /= enrichedCentroids[j].size;
+      } else {
+        enrichedCentroids[j].error = null;
+      }
     }
@@ -365,3 +374,3 @@
   );
-  var newCenters = updateCenters(data, clusterID, K);
+  var newCenters = updateCenters(centers, data, clusterID, K);
   var converged = hasConverged(
@@ -414,2 +423,3 @@ newCenters,
  * @param {string|Array<Array<number>>} [options.initialization = 'kmeans++'] - K centers in format [x,y,z,...] or a method for initialize the data:
+ *  * You can either specify your custom start centroids, or select one of the following initialization method:
  *  * `'kmeans++'` will use the kmeans++ method as described by http://ilpubs.stanford.edu:8090/778/1/2006-13.pdf
@@ -416,0 +426,0 @@ *  * `'random'` will choose K random different values.

package.json

 {
   "name": "ml-kmeans",
-  "version": "4.0.0",
+  "version": "4.0.1",
   "description": "K-Means clustering",
@@ -5,0 +5,0 @@ "main": "kmeans.js",

src/kmeans.js

@@ -38,3 +38,3 @@ import euclidean from 'ml-distance-euclidean';
   );
-  var newCenters = updateCenters(data, clusterID, K);
+  var newCenters = updateCenters(centers, data, clusterID, K);
   var converged = hasConverged(
@@ -87,2 +87,3 @@ newCenters,
  * @param {string|Array<Array<number>>} [options.initialization = 'kmeans++'] - K centers in format [x,y,z,...] or a method for initialize the data:
+ *  * You can either specify your custom start centroids, or select one of the following initialization method:
  *  * `'kmeans++'` will use the kmeans++ method as described by http://ilpubs.stanford.edu:8090/778/1/2006-13.pdf
@@ -89,0 +90,0 @@ *  * `'random'` will choose K random different values.

src/KMeansResult.js

@@ -60,3 +60,7 @@ import { updateClusterID } from './utils';
     for (var j = 0; j < this.centroids.length; j++) {
-      enrichedCentroids[j].error /= enrichedCentroids[j].size;
+      if (enrichedCentroids[j].size) {
+        enrichedCentroids[j].error /= enrichedCentroids[j].size;
+      } else {
+        enrichedCentroids[j].error = null;
+      }
     }
@@ -63,0 +67,0 @@

src/utils.js

@@ -49,2 +49,3 @@ import nearestVector from 'ml-nearest-vector';
  * @ignore
+ * @param {Array<Array<number>>} prevCenters - Centroids from the previous iteration
  * @param {Array <Array <number>>} data - the [x,y,z,...] points to cluster
@@ -55,6 +56,6 @@ * @param {Array <number>} clusterID - the cluster identifier for each data dot
  */
-export function updateCenters(data, clusterID, K) {
+export function updateCenters(prevCenters, data, clusterID, K) {
   const nDim = data[0].length;
 
-  // creates empty centers with 0 size
+  // copy previous centers
   var centers = new Array(K);
@@ -81,3 +82,7 @@ var centersLen = new Array(K);
     for (var d = 0; d < nDim; d++) {
-      centers[id][d] /= centersLen[id];
+      if (centersLen[id]) {
+        centers[id][d] /= centersLen[id];
+      } else {
+        centers[id][d] = prevCenters[id][d];
+      }
     }
@@ -84,0 +89,0 @@ }

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Improved metrics

Total package byte prevSize

38400

increased by2.8%

Lines of code

903

increased by2.27%

No dependency changes