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Active learning Decision tree/Evidence
Method evidence record

Active learning Decision tree

Active learning with a decision tree combines the interpretable structure of a CART-style tree with a query strategy that selects the most informative unlabeled instances for human annotation. The model iteratively requests labels only for examples it is most uncertain about, minimising labeling cost while maximising classification accuracy on tabular data.

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Active Learning with Decision Tree Classifier
Taxonomic method record · ml-model / machine-learning
  • Settles, B. (2010). Active Learning Literature Survey. Computer Sciences Technical Report 1648, University of Wisconsin-Madison. · URL
  • Breiman, L., Friedman, J., Olshen, R., & Stone, C. (1984). Classification and Regression Trees. Wadsworth & Brooks. · ISBN 978-0-412-04841-8
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Related methods

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Same method familyActive Learningmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketActive Learning Logistic Regressionmachine-suggested · Relational suggestion, not evidence.Same method familyDecision Treemachine-suggested · Relational suggestion, not evidence.Same method familyRandom Forestmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSemi-supervised Decision Treemachine-suggested · Relational suggestion, not evidence.

Evidence status

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Sources

2 recorded citations, copied from the method source record.

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