func LogisticRegression(c *gopark.Context) {
type dataPoint struct {
x gopark.Vector
y float64
}
points := c.TextFile("points.txt").Map(func(line interface{}) interface{} {
vs := strings.Fields(line.(string))
vector := make(gopark.Vector, len(vs)-1)
for i := 0; i < len(vs)-1; i++ {
vector[i], _ = strconv.ParseFloat(vs[i], 64)
}
y, _ := strconv.ParseFloat(vs[len(vs)-1], 64)
return &dataPoint{vector, y}
}).Cache()
hx := func(w, x gopark.Vector, y float64) float64 {
return 1/(1+math.Exp(-1*w.Dot(x))) - y
}
var w gopark.Vector = []float64{1, -10}[:]
for i := 0; i < 10; i++ {
gradient := points.Map(func(x interface{}) interface{} {
p := x.(*dataPoint)
return p.x.Multiply(-1 * hx(w, p.x, p.y))
}).Reduce(func(x, y interface{}) interface{} {
return x.(gopark.Vector).Plus(y.(gopark.Vector))
}).(gopark.Vector)
w = w.Minus(gradient)
}
fmt.Println("Final Weights:", w)
}
func CloseCenter(p gopark.Vector, centers []gopark.Vector) int {
minDist := p.EulaDistance(centers[0])
minIndex := 0
for i := 1; i < len(centers); i++ {
dist := p.EulaDistance(centers[i])
if dist < minDist {
minDist = dist
minIndex = i
}
}
return minIndex
}