predict_leaf_node_assignment path/terminal node doesn't match

[exalate-issue-sync]

It’s possible for {{model.predict_leaf_node_assignment(df, type='path')}} to produce a different number of unique elements than {{model.predict_leaf_node_assignment(df, type='Node_ID')}}.

{code:python}import h2o
from h2o.estimators.random_forest import H2ORandomForestEstimator
from h2o.tree import H2OTree

h2o.init(min_mem_size='5G')

model = H2ORandomForestEstimator(
ntrees = 1,
max_depth = 1000
)

df = h2o.import_file('/Users/jgranados/datasets/kaggle/ieee-fraud-detection/train_transaction.csv')

x = df.columns
y = 'isFraud'
x.remove(y)

model.train(x=x, y=y, training_frame=df)

tree = H2OTree(model = model, tree_number = 0)

path_assignment = model.predict_leaf_node_assignment(df, type='path')
node_assignment = model.predict_leaf_node_assignment(df, type='Node_ID')

len(path_assignment.unique()) == len(node_assignment.unique()){code}

[exalate-issue-sync]

Satish Maruvada commented: Could we implement this a part of a patch release? The customer has/is pinging us multiple times for this. [~accountid:5d3a21774ee45b0c8fec4afb] fyi!

[exalate-issue-sync]

Niki Athanasiadou commented: Yes, there is a lot of interest in leaf node path assignments there, for h2o-3 as well as DAI. Thanks [~accountid:5d6fedeb294c590c3ae52968].

[exalate-issue-sync]

Michal Kurka commented: Fixed for tree with {{max_depth}} to 63. For {{max_depth}} 64 or higher the code will no longer produce incorrect results, it will instead return {{NA}} for tree paths and {{-1}} for node ids (for path and nodes that “too” deep).

[~accountid:5d6fedeb294c590c3ae52968] [~accountid:5d3a21774ee45b0c8fec4afb] it is able to make the code work for any tree depth, however, this change is more involved and IMHO out of the scope of a fix release. If such functionality is desired please file a new jira.

[exalate-issue-sync]

Michal Kurka commented: [~accountid:557058:6e44bc1a-dd50-499b-a331-2e049f28773b] what would be good place to document these limitations?

[exalate-issue-sync]

Angela Bartz commented: [~accountid:557058:04659f86-fbfe-4d01-90c9-146c34df6ee6] I think it can go in a couple of places. We can add a note in the "Predict Leaf Node Assignment" section:
https://github.com/h2oai/h2o-3/blob/master/h2o-docs/src/product/performance-and-prediction.rst#predicting-leaf-node-assignment

I think we can also add information about how the value of max_depth affects leaf node prediction in the max_depth parameter appendix entry:
https://github.com/h2oai/h2o-3/blob/master/h2o-docs/src/product/data-science/algo-params/max_depth.rst

[h2o-ops]

JIRA Issue Migration Info

Jira Issue: PUBDEV-7590
Assignee: Michal Kurka
Reporter: Joseph Granados
State: Resolved
Fix Version: 3.30.0.5
Attachments: N/A
Development PRs: Available

Linked PRs from JIRA

#4673
#4679
#4694