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Https://stat.ethz.ch /education/semesters /ss2012/ams/slides/v 10.2.pdf

v10.2.pdf

🔗 Source: stat.ethz.ch

📊 Size: 525 KB

👤 Author: kalischm

⬇️ Downloads: 539

Summary

Random Forest consists of intuition, algorithm, and key concepts. The intuition involves combining multiple tree predictions to make a final prediction, such as classifying a new sample as "diseased" based on majority rule. The Random Forest Algorithm differs from standard trees in that it trains each tree on a bootstrap resample of data, considers only randomly selected variables for each split, and doesn't prune. It fits multiple trees and aggregates results through average or majority voting, also utilizing out-of-bag error and variable importance for evaluation.

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Description

Random Forest consists of intuition, algorithm, and key concepts.

Technical Information

File Format: PDF
File Size: 525 KB
Pages: 14
Language: EN
Author: kalischm
Total Downloads: 539
Last Updated: 3 hours ago

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