[
https://issues.apache.org/jira/browse/HIVEMALL-245?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16919836#comment-16919836
]
ASF GitHub Bot commented on HIVEMALL-245:
-----------------------------------------
myui commented on issue #198: [WIP][HIVEMALL-245] Refactor RandomForest for
Sparse Data handling
URL:
https://github.com/apache/incubator-hivemall/pull/198#issuecomment-526717670
```
Caused by: java.lang.IndexOutOfBoundsException: low=0, pivot=215, high=4747,
a.length=2, buf.length=4532, k=2
at
hivemall.smile.classification.DecisionTree.partitionArray(DecisionTree.java:1051)
at
hivemall.smile.classification.DecisionTree.access$1700(DecisionTree.java:119)
at
hivemall.smile.classification.DecisionTree$TrainNode$4.accept(DecisionTree.java:996)
at hivemall.smile.utils.VariableOrder.eachRow(VariableOrder.java:41)
at
hivemall.smile.classification.DecisionTree$TrainNode.partitionOrder(DecisionTree.java:993)
at
hivemall.smile.classification.DecisionTree$TrainNode.split(DecisionTree.java:896)
at
hivemall.smile.classification.DecisionTree.<init>(DecisionTree.java:1269)
at
hivemall.smile.classification.RandomForestClassifierUDTF$TrainingTask.call(RandomForestClassifierUDTF.java:536)
at
hivemall.smile.classification.RandomForestClassifierUDTF$TrainingTask.call(RandomForestClassifierUDTF.java:474)
... 4 more
```
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> Refactor RandomForest for Sparse Data handling
> ----------------------------------------------
>
> Key: HIVEMALL-245
> URL: https://issues.apache.org/jira/browse/HIVEMALL-245
> Project: Hivemall
> Issue Type: Improvement
> Affects Versions: 0.5.2
> Reporter: Makoto Yui
> Assignee: Makoto Yui
> Priority: Major
> Fix For: 0.6.0
>
>
> * Fix attribute to use RoaringBitmap instead of AttributeType[]
> * Support pruning of redundant decision tree nodes
> * Support the default value for missing values
> * Fix split handling of sparse numeric values
> ** problem: split does not occur when column values have a single value
> *** if(x<=1.0) \{ .. } else \{ ... } never split where sparse x is already
> 1.0
> ** if there are only a single value for a column, then treat it as nominal
> value (?)
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