Decision tree classifier implementation in Go language.
== Input == float64 predictor values, categorical (0/1) target values
== Output == Classifier
Usage:
import 'rtree'
... observations := loadSomeObservations() t := new(rtree) t.InitRoot(getSettings("supergrow"), *observations).Expand(true) ... t.Classify(map[string]*Value{ "attr1": &Value{1.0}, "attr2": &Value{17.0}, })