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Xiangrui Meng resolved SPARK-2756. ---------------------------------- Resolution: Fixed Fix Version/s: 1.1.0 Issue resolved by pull request 1673 [https://github.com/apache/spark/pull/1673] > Decision Tree bugs > ------------------ > > Key: SPARK-2756 > URL: https://issues.apache.org/jira/browse/SPARK-2756 > Project: Spark > Issue Type: Bug > Components: MLlib > Affects Versions: 1.0.0 > Reporter: Joseph K. Bradley > Assignee: Joseph K. Bradley > Fix For: 1.1.0 > > > 3 bugs: > Bug 1: Indexing is inconsistent for aggregate calculations for unordered > features (in multiclass classification with categorical features, where the > features had few enough values such that they could be considered unordered, > i.e., isSpaceSufficientForAllCategoricalSplits=true). > * updateBinForUnorderedFeature indexed agg as (node, feature, featureValue, > binIndex), where > ** featureValue was from arr (so it was a feature value) > ** binIndex was in [0,…, 2^(maxFeatureValue-1)-1) > * The rest of the code indexed agg as (node, feature, binIndex, label). > Bug 2: calculateGainForSplit (for classification): > * It returns dummy prediction values when either the right or left children > had 0 weight. These are incorrect for multiclass classification. > Bug 3: Off-by-1 when finding thresholds for splits for continuous features. > * When finding thresholds for possible splits for continuous features in > DecisionTree.findSplitsBins, the thresholds were set according to individual > training examples’ feature values. This can cause problems for small > datasets. -- This message was sent by Atlassian JIRA (v6.2#6252)