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A few years ago I read a book on artificial intelligence algorithms (Artificial Intelligence for Humans) and had it on my todo list to implement a couple of the algorithms.
There's lots of implementations out there already in Go, but I've always found that writing an implementation makes sure I understand how something really works and why existing implementations are designed the way they are, or what problems to look out for.
So far, I've implemented KMeans clustering and a few distance metrics to use: Chebyshev (Chessboard), Euclidean and Manhattan.
Here's some example code which produces the PNG graph above.
package main
import (
"fmt"
"math/rand"
"os"
"strconv"
"time"
"github.com/a-h/ml/clustering"
"github.com/a-h/ml/distance"
"gonum.org/v1/plot"
"gonum.org/v1/plot/plotter"
"gonum.org/v1/plot/plotutil"
"gonum.org/v1/plot/vg"
)
func init() {
rand.Seed(time.Now().Unix())
}
func main() {
p, err := plot.New()
if err != nil {
fmt.Println("Error creating Plot: ", err)
os.Exit(-1)
}
p.Title.Text = "KMeans"
p.X.Min = 0
p.X.Padding = 0
p.X.Label.Text = "X"
p.Y.Min = 0
p.Y.Padding = 0
p.Y.Label.Text = "Y"
// Create some random data and assign to n clusters.
data := random2DVectors(50)
n := 3
assignment, err := clustering.KMeans(data, n, distance.Euclidean)
if err != nil {
fmt.Println("Error clustering data: ", err)
os.Exit(-1)
}
// Get the clusters.
clusters, err := clustering.Assign(data, assignment)
if err != nil {
fmt.Println("Error assigning data to clusters: ", err)
os.Exit(-1)
}
// Convert them to scatter inputs (something that implements the XYer interface).
for i, cluster := range clusters {
scatter := convert2DVectorToPlotterXY(cluster)
// Add them to the chart.
err = addScatters(p, i, strconv.Itoa(i+1), scatter)
if err != nil {
panic(err)
}
}
// Save the plot to a PNG file.
if err := p.Save(15*vg.Centimeter, 15*vg.Centimeter, "points.png"); err != nil {
panic(err)
}
}
func convert2DVectorToPlotterXY(v []clustering.Vector) plotter.XYs {
pts := make(plotter.XYs, len(v))
for i := 0; i < len(v); i++ {
pts[i] = xy{
X: v[i][0],
Y: v[i][1],
}
}
return pts
}
type xy struct {
X, Y float64
}
func random2DVectors(n int) []clustering.Vector {
op := make([]clustering.Vector, n)
for i := 0; i < n; i++ {
v := make(clustering.Vector, 2)
randomise(v, -10, 10)
op[i] = v
}
return op
}
func randomise(v []float64, min, max int) {
for i := 0; i < len(v); i++ {
v[i] = float64(rand.Intn(max-min) + min)
}
}
func addScatters(plt *plot.Plot, index int, name string, xyers plotter.XYs) error {
s, err := plotter.NewScatter(xyers)
if err != nil {
return err
}
s.Color = plotutil.Color(index)
s.Shape = plotutil.Shape(index)
plt.Add(s)
plt.Legend.Add(name)
return nil
}
The code is up at [0]
I'll be adding more functions when I feel like it.
Grafana - Why is my singlestat panel showing a decimal / float instead of an integer?