Hi James,
It's a good idea. A JSON format is more convenient for visualization though a
little inconvenient to read. How about toJson() method? It might make the mllib
api inconsistent across models though.
You should probably create a JIRA for this.
CC: dev list
-Manish
> On Aug 26, 2015, at 11:29 AM, Murphy, James <james.mur...@disney.com> wrote:
>
> Hey all,
>
> In working with the DecisionTree classifier, I found it difficult to extract
> rules that could easily facilitate visualization with libraries like D3.
>
> So for example, using : print(model.toDebugString()), I get the following
> result =
>
> If (feature 0 <= -35.0)
> If (feature 24 <= 176.0)
> Predict: 2.1
> If (feature 24 = 176.0)
> Predict: 4.2
> Else (feature 24 > 176.0)
> Predict: 6.3
> Else (feature 0 > -35.0)
> If (feature 24 <= 11.0)
> Predict: 4.5
> Else (feature 24 > 11.0)
> Predict: 10.2
>
> But ideally, I could see results in a more parseable format like JSON:
>
> {
> "node": [
> {
> "name":"node1",
> "rule":"feature 0 <= -35.0",
> "children":[
> {
> "name":"node2",
> "rule":"feature 24 <= 176.0",
> "children":[
> {
> "name":"node4",
> "rule":"feature 20 < 116.0",
> "predict": 2.1
> },
> {
> "name":"node5",
> "rule":"feature 20 = 116.0",
> "predict": 4.2
> },
> {
> "name":"node5",
> "rule":"feature 20 > 116.0",
> "predict": 6.3
> }
> ]
> },
> {
> "name":"node3",
> "rule":"feature 0 > -35.0",
> "children":[
> {
> "name":"node7",
> "rule":"feature 3 <= 11.0",
> "predict": 4.5
> },
> {
> "name":"node8",
> "rule":"feature 3 > 11.0",
> "predict": 10.2
> }
> ]
> }
>
> ]
> }
> ]
> }
>
> Food for thought!
>
> Thanks,
>
> Jim
>
