Across
- 1. A method to split data into multiple subsets for model evaluation (16)
- 4. A metric that measures the overall accuracy of a model (7)
- 5. A type of error where a model incorrectly predicts a negative case as positive (12)
- 7. A metric that measures the ability of a model to avoid false positives (8)
- 9. A type of machine learning problem where the goal is to predict a continuous value
- 10. A metric that measures the ability of a model to correctly identify all positive cases (5)
- 12. A machine learning problem where the goal is to predict a categorical value (13)
- 15. The process of finding the best model for a specific problem (13)
- 16. A type of model evaluation where the model is trained on a subset of the data and tested on the remaining subset (7)
Down
- 2. The process of gathering data for model training (14)
- 3. The process of preparing data for model training (16)
- 6. The process of improving model performance by adjusting parameters
- 8. A matrix used to evaluate classification model performance (14)
- 11. A metric that measures the ability of a model to correctly identify positive cases (5)
- 13. A type of error where a model incorrectly predicts a positive case as negative (13)
- 14. A machine learning problem where the goal is to assign data points to groups (9)
