Machine Learning Model Selection Quiz

What does ML model selection help avoid?

• Overfitting or underfitting

• Overheating or underheating

• Oversleeping or undersleeping

• Overeating or undereating

What does ML model selection optimize?

• Bias-variance trade-off

• Speed-accuracy trade-off

• Price-performance trade-off

• Quality-quantity trade-off

What does ML model selection ensure?

• Predictive performance is generalizable to unseen real-world data

• Predictive performance is limited to seen real-world data

• Predictive performance is limited to unseen real-world data

• Predictive performance is generalizable to seen real-world data

What does ML model selection help balance?

• Model’s performance and cost of computational resources

• Model’s performance and time taken to build the model

• Model’s performance and number of features used

• Model’s performance and number of iterations

What can occur if the model is poorly trained?

• Overfitting or underfitting

• Accuracy or precision

• Generalization or specialization

• Optimization or underperformance