Machine learning terms/Decision Forests: Difference between revisions
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Revision as of 16:43, 26 February 2023
- attribute sampling
- axis-aligned condition
- bagging
- binary condition
- condition
- decision forest
- decision tree
- entropy
- feature importances
- gini impurity
- gradient boosting
- gradient boosted (decision) trees (GBT)
- inference path
- information gain
- in-set condition
- leaf
- node (decision tree)
- non-binary condition
- oblique condition
- out-of-bag evaluation (OOB evaluation)
- permutation variable importances
- random forest
- root
- sampling with replacement
- shrinkage
- split
- splitter
- test
- threshold (for decision trees)
- variable importances
- wisdom of the crowd