Better handling of Categorical attributes when building Decision Forests
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Key: MAHOUT-245
URL: https://issues.apache.org/jira/browse/MAHOUT-245
Project: Mahout
Issue Type: Improvement
Components: Classification
Affects Versions: 0.3
Reporter: Deneche A. Hakim
Assignee: Deneche A. Hakim
Fix For: 0.3
When building a decision tree, at each node a random subset from all variables
(attributes) is considered for the node split.
If a Categorical variable has been selected, the data available at the node is
split such that each child node has the same value for the selected variable.
In all sub-nodes the selected variable should not be selected again, but the
current implementation does not account for that. The resulting tree may
contain redundant nodes that does not impair its classification performance but
are nonetheless unnecessary.
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