Machine Learning Glossary/Decision Forests

Verfasst von / Written by Sebastian F. Genter

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• Machine Learning Glossary

This page functions as an index and presents a systematic listing of the entries found in the main glossary or on the main page.

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A

• attribute sampling
• axis-aligned condition

B

• bagging
• binary condition

C

• condition

D

• decision forest
• decision tree

E

• entropy

F

• feature importances

G

• gini impurity
• gradient boosted (decision) trees (GBT)
• gradient boosting

I

• inference path
• information gain
• in-set condition

L

• leaf

N

• node (decision tree)
• non-binary condition

O

• oblique condition
• out-of-bag evaluation (OOB evaluation)

P

• permutation variable importances

R

• random forest
• root

S

• sampling with replacement
• shrinkage
• split
• splitter

T

• test
• threshold (for decision trees)

V

• variable importances

W

• wisdom of the crowd