func main() {
sumR := 0.0
sum3 := 0.0
sum5 := 0.0
sum10 := 0.0
for _, importer := range load.Ambiant {
corpus := importer.Import()
dpmom := cluster.NewDPMoM(corpus, 1, 20, .2, .2)
graphical.RunCCM(dpmom, cluster.NewConvergenceCheck(dpmom.Z), 0)
gold := importer.Label(corpus)
pred := eval.NewClusteringState(dpmom.Z)
cont := eval.NewContingency(gold, pred)
rerank := eval.Rerank(dpmom.Z)
sumR += cont.Rand()
sum3 += eval.SRecallK(3, rerank, gold)
sum5 += eval.SRecallK(5, rerank, gold)
sum10 += eval.SRecallK(10, rerank, gold)
}
n := float64(len(load.Ambiant))
fmt.Println("Rand :", sumR/n)
fmt.Println("SR@3 :", sum3/n)
fmt.Println("SR@5 :", sum5/n)
fmt.Println("SR@10:", sum10/n)
}
func (r Runner) EvalQuery(importer load.Importer) Stats {
corpus := importer.Import()
gold := importer.Label(corpus)
z := r(corpus)
pred := eval.NewClusteringState(z)
cont := eval.NewContingency(gold, pred)
rerank := eval.Rerank(z)
stats := Stats{}
stats.Rand = cont.Rand()
for i, k := range Ks {
stats.Recall[i] = eval.SRecallK(k, rerank, gold)
}
return stats
}