densitytarget.go

package CloudForest

import (
	"fmt"
)

/*
DensityTarget is used for density estimating trees. It contains a set of features and the
count of cases.
*/
type DensityTarget struct {
	Features *[]Feature
	N        int
}

func (target *DensityTarget) GetName() string {
	return "DensityTarget"
}

/*
DensityTarget.SplitImpurity is a density estimating version of SplitImpurity.
*/
func (target *DensityTarget) SplitImpurity(l *[]int, r *[]int, m *[]int, allocs *BestSplitAllocs) (impurityDecrease float64) {
	nl := float64(len(*l))
	nr := float64(len(*r))
	nm := 0.0

	impurityDecrease = nl * target.Impurity(l, nil)
	impurityDecrease += nr * target.Impurity(r, nil)
	if m != nil && len(*m) > 0 {
		nm = float64(len(*m))
		impurityDecrease += nm * target.Impurity(m, nil)
	}

	impurityDecrease /= nl + nr + nm
	return
}

//UpdateSImpFromAllocs willl be called when splits are being built by moving cases from r to l as in learning from numerical variables.
//Here it just wraps SplitImpurity but it can be implemented to provide further optimization.
func (target *DensityTarget) UpdateSImpFromAllocs(l *[]int, r *[]int, m *[]int, allocs *BestSplitAllocs, movedRtoL *[]int) (impurityDecrease float64) {
	return target.SplitImpurity(l, r, m, allocs)
}

//DensityTarget.Impurity uses the impurity measure defined in "Density Estimating Trees"
//by Parikshit Ram and Alexander G. Gray
func (target *DensityTarget) Impurity(cases *[]int, counter *[]int) (e float64) {
	t := len(*cases)
	e = float64(t*t) / float64(target.N*target.N)
	for _, f := range *target.Features {
		switch f.(type) {
		case CatFeature:
			bigenoughcounter := make([]int, f.NCats())
			e /= f.Span(cases, &bigenoughcounter)
		case NumFeature:
			e /= f.Span(cases, nil)
		}
	}

	return
}

//DensityTarget.FindPredicted returns the string representation of the density in the region
//spaned by the specified cases.
func (target *DensityTarget) FindPredicted(cases []int) string {
	t := len(cases)
	e := float64(t) / float64(target.N)

	for _, f := range *target.Features {
		switch f.(type) {
		case CatFeature:
			bigenoughcounter := make([]int, f.NCats())
			e /= f.Span(&cases, &bigenoughcounter)
		case NumFeature:
			e /= f.Span(&cases, nil)
		}
	}

	return fmt.Sprintf("%v", e)
}

func (target *DensityTarget) NCats() int {
	return 0
}