func ChiMBuildFrequencyTable(attr int, inst *base.Instances) []*FrequencyTableEntry {
ret := make([]*FrequencyTableEntry, 0)
var attribute *base.FloatAttribute
attribute, ok := inst.GetAttr(attr).(*base.FloatAttribute)
if !ok {
panic("only use Chi-M on numeric stuff")
}
for i := 0; i < inst.Rows; i++ {
value := inst.Get(i, attr)
valueConv := attribute.GetUsrVal(value)
class := inst.GetClass(i)
// Search the frequency table for the value
found := false
for _, entry := range ret {
if entry.Value == valueConv {
found = true
entry.Frequency[class] += 1
}
}
if !found {
newEntry := &FrequencyTableEntry{
valueConv,
make(map[string]int),
}
newEntry.Frequency[class] = 1
ret = append(ret, newEntry)
}
}
return ret
}
func main() {
// Load in the iris dataset
iris, err := base.ParseCSVToInstances("../datasets/iris_headers.csv", true)
if err != nil {
panic(err)
}
for _, a := range iris.AllAttributes() {
// var ac base.CategoricalAttribute
var af base.FloatAttribute
s, err := json.Marshal(a)
if err != nil {
panic(err)
}
fmt.Println(string(s))
err = json.Unmarshal(s, &af)
fmt.Println(af.String())
// err = json.Unmarshal(s, &ac)
// fmt.Println(ac.String())
}
}