What are the main challenges in predictive modeling?

What are the main challenges in predictive modeling?

Some key challenges include data quality, overfitting, feature selection, and model interpretability.

Can you explain how data quality affects predictive modeling?

Data quality is crucial; poor data can lead to inaccurate predictions and unreliable models.

What is overfitting and how can it be avoided?

Overfitting occurs when a model learns noise instead of the signal. It can be avoided by using techniques like cross-validation.

How important is feature selection in building a predictive model?

Feature selection is vital as it helps improve model performance and reduces complexity by eliminating irrelevant data.