Ensemble Learning

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Across
  1. 3. Process of sampling with replacement used in bagging
  2. 5. Random Forest reduces which type of error
  3. 6. Simple combination method using average of predictions
  4. 10. Ensemble method used in the gradient descent framework
  5. 12. A weak learner commonly used in boosting
  6. 14. Extreme version of Gradient Boosting algorithm
  7. 15. Most common algorithm used in bagging
  8. 16. Technique that combines multiple models to improve accuracy
Down
  1. 1. Ensemble method that builds models in parallel
  2. 2. Combining model predictions using majority vote
  3. 4. Algorithm based on combining weak learners to make a strong one
  4. 7. In stacking, the final model that combines base learners
  5. 8. Boosting mainly reduces which type of error
  6. 9. Combination of different types of models
  7. 11. Ensemble algorithm known for speed and efficiency
  8. 13. Ensemble method that builds models sequentially