What factors could make a prediction model less accurate?
Several factors can contribute to reduced accuracy in a prediction model. Here are some key issues to consider:
Insufficient or poor-quality data:
- Too little data to capture patterns effectively
- Inaccurate, inconsistent, or biased data
Overfitting:
- Model learns noise in training data too precisely
- Performs well on training data but poorly on new, unseen data
Underfitting:
- Model is too simple to capture the underlying patterns
- Fails to learn important relationships in the data