Across
- 3. What are model settings that are set before training begins and not learned from data called?
- 4. is a Python library for machine learning
- 5. When a model is too complex and overly sensitive to training data noise, this problem is called what?
- 7. This process combines multiple models to improve performance and reduce errors.
- 8. This dimensionality reduction technique identifies patterns and transforms data into a lower-dimensional space.
- 9. Matrix summarizes classification model predictions.
- 10. When a model is too simple and makes overly simplistic assumptions, resulting in high training and test errors, this is called what?
Down
- 1. This technique reduces overfitting by adding a penalty term to the model's cost function.
- 2. This technique evaluates model performance by splitting the dataset into multiple training and validation sets.7. MSE This metric measures overall correctness in classification problems.
- 6. This bagging ensemble model combines multiple decision trees.