func main() {
train, test, pred, method, params := hector.PrepareParams()
action, _ := params["action"]
classifier := hector.GetMutliClassClassifier(method)
profile, _ := params["profile"]
if profile != "" {
fmt.Printf("Profile data => %s\n", profile)
f, err := os.Create(profile)
if err != nil {
log.Fatal(err)
}
pprof.StartCPUProfile(f)
defer pprof.StopCPUProfile()
}
if action == "" {
accuracy, _ := hector.MultiClassRun(classifier, train, test, pred, params)
fmt.Println("accuracy : ", accuracy)
} else if action == "train" {
hector.MultiClassTrain(classifier, train, params)
} else if action == "test" {
accuracy, _ := hector.MultiClassTest(classifier, test, pred, params)
fmt.Println("accuracy", accuracy)
}
}
func main() {
train_path, _, _, method, params := hector.PrepareParams()
global, _ := strconv.ParseInt(params["global"], 10, 64)
profile, _ := params["profile"]
dataset := core.NewDataSet()
dataset.Load(train_path, global)
cv, _ := strconv.ParseInt(params["cv"], 10, 32)
total := int(cv)
if profile != "" {
f, err := os.Create(profile)
if err != nil {
log.Fatal(err)
}
pprof.StartCPUProfile(f)
defer pprof.StopCPUProfile()
}
average_accuracy := 0.0
for part := 0; part < total; part++ {
train, test := SplitFile(dataset, total, part)
classifier := hector.GetMutliClassClassifier(method)
classifier.Init(params)
accuracy := hector.MultiClassRunOnDataSet(classifier, train, test, "", params)
fmt.Println("accuracy : ", accuracy)
average_accuracy += accuracy
classifier = nil
train = nil
test = nil
runtime.GC()
}
fmt.Println(average_accuracy / float64(total))
}