Details
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Umbrella
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Status: Resolved
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Major
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Resolution: Incomplete
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None
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None
Description
This is an umbrella for improvements to learning Random Forests: RandomForestClassifier, RandomForestRegressor.
Note: Aspects of RFs which are related to individual trees should be listed under SPARK-14045.
Attachments
Issue Links
- contains
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SPARK-9623 RandomForestRegressor: provide variance of predictions
- Resolved
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SPARK-20081 RandomForestClassifier doesn't seem to support more than 100 labels
- Resolved
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SPARK-16719 RandomForest: communicate fewer trees on each iteration
- Resolved
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SPARK-9478 Add sample weights to Random Forest
- Resolved
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SPARK-13434 Reduce Spark RandomForest memory footprint
- Resolved
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SPARK-13868 Random forest accuracy exploration
- Resolved
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SPARK-3723 DecisionTree, RandomForest: Add more instrumentation
- Resolved
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SPARK-3724 RandomForest: More options for feature subset size
- Resolved
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SPARK-3728 RandomForest: Learn models too large to store in memory
- Resolved
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SPARK-23704 PySpark access of individual trees in random forest is slow
- Resolved
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SPARK-23730 Save and expose "in bag" tracking for random forest model
- Resolved
- relates to
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SPARK-34591 Pyspark undertakes pruning of decision trees and random forests outside the control of the user, leading to undesirable and unexpected outcomes that are challenging to diagnose and impossible to correct
- In Progress
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SPARK-14045 DecisionTree improvement umbrella
- Resolved