Overfitting In Trees
Overfitting in Trees is a modeling phenomenon in machine learning where a decision tree learns training data patterns so intricately that it captures noise and irrelevant fluctuations, thereby compromising its generalization to unseen data.
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Trading Accuracy for Simplicity in Decision Trees
Marko Bohanec, Ivan Bratko · Machine Learning · 1994 · 141 citations · Full text
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Jožef Stefan Institute
Ljubljana, Slovenia
3 h-index
5 publications
436 citations

University of Ljubljana
Ljubljana, Slovenia
2 h-index
2 publications
223 citations
Nokia (United States)
Coppell, United States
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2 publications
6.9K citations

Télécom Paris
Palaiseau, France
1 h-index
1 publications
13 citations

Policlinico Umberto I
Rome, Italy
1 h-index
9 publications
207 citations
IMDEA Networks
Leganés, Spain
1 h-index
1 publications
69 citations
University of Science and Technology of China
Hefei, China
1 h-index
2 publications
160 citations
Dongseo University
Busan, South Korea
1 h-index
1 publications
10 citations
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3 publications · 142 citations
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2 publications · 223 citations
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TPAMI · 2 publications · 7K citations
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2 publications · 156 citations
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Repository · 1 publications · 82 citations
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