I’m trying to use Spark ml to create a classification tree model and examine the resulting model.
I have managed to create a DecisionTreeClassificationModel (class org.apache.spark.ml.classification.DecisionTreeClassificationModel), but have not been able to obtain basic information from the model. For example, I am able to obtain the root node of the tree via the ‘rootNode’ field. But how do I get to other nodes? If I get to a Node object ( class = org.apache.park.ml.tree.Node ), how do I get essential information from a particular node, such as what are the counts or probabilities of each of the target classes at that node in the training data? It seems like the only piece of info I’m allowed to know is the predicted class, via the ‘prediction’ field. Randy Kerber ----- Randy Kerber Data Science Consultant San Jose, California -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Getting-info-from-DecisionTreeClassificationModel-tp25152.html Sent from the Apache Spark User List mailing list archive at Nabble.com.
