Download cs229 Notes Ensemble PDF Free - Full Version
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About cs229 Notes Ensemble
This document discusses ensemble methods for machine learning models. It covers bagging and boosting techniques. Bagging (bootstrap aggregation) trains models on randomly sampled subsets of the data and averages their predictions to reduce variance. Boosting sequentially trains weak learners like decision stumps to reduce bias. Both techniques can improve on a single model's accuracy by reducing correlated errors.
Detailed Information
| Author: | ['bob'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 7 |
| Language: | English |
| Format: | |
| Price: | FREE |
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