minor refactor

README.md

@@ -1,5 +1,6 @@
 # Go Kmeans
 
+[![Go Reference](https://pkg.go.dev/badge/github.com/arjunsk/kmeans/kmeans.svg)](https://pkg.go.dev/github.com/arjunsk/kmeans)
 [![Go Report Card](https://goreportcard.com/badge/github.com/arjunsk/kmeans)](https://goreportcard.com/report/github.com/arjunsk/kmeans)
 
 This is a simple implementation of the [Elkan's Kmeans](https://cdn.aaai.org/ICML/2003/ICML03-022.pdf)

clusterer/elkan.go

@@ -17,7 +17,7 @@ type KmeansElkan struct {
 
 	assignments []int       // maps vector index to cluster index
 	lowerBounds [][]float64 // distances for vector and all clusters centroids
-	upperBounds []float64   // distance between each point and its assigned cluster centroid
+	upperBounds []float64   // distance between each point and its assigned cluster centroid ie d(x, c(x))
 	r           []bool      // indicates that upper bound needs to be recalculated
 
 	// local state
@@ -99,7 +99,7 @@ func (el *KmeansElkan) kmeansElkan(clusters containers.Clusters) error {
 		// step 4
 		// For each center c, let m(c) be the mean of the points assigned to c.
 		// step 7
-		// Replace each center $c$ by $m(c)$.
+		// Replace each center c by m(c).
 		moveDistances, err := clusters.RecenterWithDeltaDistance(el.distFn)
 		if err != nil {
 			return err

options.go

@@ -8,8 +8,8 @@ import (
 )
 
 var (
-	DefaultDeltaThreshold     = 0.01
-	DefaultIterationThreshold = 500
+	defaultDeltaThreshold     = 0.01
+	defaultIterationThreshold = 500
 )
 
 type ClustererType int
@@ -38,10 +38,10 @@ func (o *options) fillDefaults() {
 		o.distanceFn = containers.EuclideanDistance
 	}
 	if o.deltaThreshold == nil {
-		o.deltaThreshold = &DefaultDeltaThreshold
+		o.deltaThreshold = &defaultDeltaThreshold
 	}
 	if o.iterationThreshold == nil {
-		o.iterationThreshold = &DefaultIterationThreshold
+		o.iterationThreshold = &defaultIterationThreshold
 	}
 
 }